title stringlengths 3 261 | abstract stringlengths 24 4.17k | label class label 8
classes |
|---|---|---|
Generalisable Cardiac Structure Segmentation via Attentional and Stacked
Image Adaptation | Tackling domain shifts in multi-centre and multi-vendor data sets remains
challenging for cardiac image segmentation. In this paper, we propose a
generalisable segmentation framework for cardiac image segmentation in which
multi-centre, multi-vendor, multi-disease datasets are involved. A generative
adversarial netwo... | 22 |
Sequential Wnt Agonist then Antagonist Treatment Accelerates Tissue
Repair and Minimizes Fibrosis | Tissue fibrosis compromises organ function and occurs as a potential
long-term outcome in response to acute tissue injuries. Currently, lack of
mechanistic understanding prevents effective prevention and treatment of the
progression from acute injury to fibrosis. Here, we combined quantitative
experimental studies wi... | 55 |
Retention Time of Peptides in Liquid Chromatography Is Well Estimated
upon Deep Transfer Learning | A fully automatic prediction for peptide retention time (RT) in liquid
chromatography (LC), termed as DeepRT, was developed using deep learning
approach, an ensemble of Residual Network (ResNet) and Long Short-Term Memory
(LSTM). In contrast to the traditional predictor based on the hand-crafted
features for peptides... | 55 |
An Adversarial Approach to Structural Estimation | We propose a new simulation-based estimation method, adversarial estimation,
for structural models. The estimator is formulated as the solution to a minimax
problem between a generator (which generates simulated observations using the
structural model) and a discriminator (which classifies whether an observation
is s... | 11 |
Mackey functors for posets | We characterize cofibrant objects in the category of functors indexed in a
filtered poset and we show that these objects are acyclic. As a consequence, we
show that Mackey functors over posets are also acyclic, where we define this
type of Mackey functors mimicking the classical notion. As application, we
study homot... | 33 |
Asymmetric uncertainty : Nowcasting using skewness in real-time data | This paper presents a new way to account for downside and upside risks when
producing density nowcasts of GDP growth. The approach relies on modelling
location, scale and shape common factors in real-time macroeconomic data. While
movements in the location generate shifts in the central part of the predictive
density... | 11 |
Hydrogen and Battery Storage Technologies for Low Cost Energy
Decarbonization in Distribution Networks | Deep energy decarbonization cannot be achieved without high penetration of
renewables. At higher renewable energy penetrations, the variability and
intermittent nature of solar photovoltaic (PV) electricity can cause ramping
issues with existing fossil fuel generation, requiring longer term energy
storage to increase... | 22 |
Why and When LLM-Based Assistants Can Go Wrong: Investigating the
Effectiveness of Prompt-Based Interactions for Software Help-Seeking | Large Language Model (LLM) assistants, such as ChatGPT, have emerged as
potential alternatives to search methods for helping users navigate complex,
feature-rich software. LLMs use vast training data from domain-specific texts,
software manuals, and code repositories to mimic human-like interactions,
offering tailore... | 00 |
Two-stream Network for ECG Signal Classification | Electrocardiogram (ECG), a technique for medical monitoring of cardiac
activity, is an important method for identifying cardiovascular disease.
However, analyzing the increasing quantity of ECG data consumes a lot of
medical resources. This paper explores an effective algorithm for automatic
classifications of multi-... | 22 |
One-sided convergence in the Boltzmann-Grad limit | We review various contributions on the fundamental work of Lanford deriving
the Boltzmann equation from hard-sphere dynamics in the low density limit. We
focus especially on the assumptions made on the initial data and on how they
encode irreversibility. The impossibility to reverse time in the Boltzmann
equation (ex... | 33 |
An Intent Modeling and Inference Framework for Autonomous and Remotely
Piloted Aerial Systems | An intent modelling and inference framework is presented to assist the
defense planning for protecting a geo-fence against unauthorized flights.
First, a novel mathematical definition for the intent of an uncrewed aircraft
system (UAS) is presented. The concepts of critical waypoints and critical
waypoint patterns ar... | 22 |
Estimation of Absolute States of Human Skeletal Muscle via Standard
B-Mode Ultrasound Imaging and Deep Convolutional Neural Networks | Objective: To test automated in vivo estimation of active and passive
skeletal muscle states using ultrasonic imaging. Background: Current technology
(electromyography, dynamometry, shear wave imaging) provides no general,
non-invasive method for online estimation of skeletal intramuscular states.
Ultrasound (US) all... | 22 |
Deep Ensemble approach for Enhancing Brain Tumor Segmentation in
Resource-Limited Settings | Segmentation of brain tumors is a critical step in treatment planning, yet
manual segmentation is both time-consuming and subjective, relying heavily on
the expertise of radiologists. In Sub-Saharan Africa, this challenge is
magnified by overburdened medical systems and limited access to advanced
imaging modalities a... | 22 |
Fractional Vegetation Cover Estimation using Hough Lines and Linear
Iterative Clustering | A common requirement of plant breeding programs across the country is
companion planting -- growing different species of plants in close proximity so
they can mutually benefit each other. However, the determination of companion
plants requires meticulous monitoring of plant growth. The technique of ocular
monitoring ... | 00 |
AI Plays? {\delta}-Rationality Games with Nash Equilibrium as Special Case | A distortion function, which captures the payoff gap between a player's actual payoff and her true payoff, is introduced and used to analyze games. In our proposed framework, we argue that players' actual payoff functions should be used to explain and predict their behaviors, while their true payoff functions should be... | 11 |
Common Idiosyncratic Quantile Factors and Asset Prices | We investigate whether the tails of firm-level idiosyncratic return distributions are driven by common shocks. We use quantile factor analysis to extract such common idiosyncratic quantile factors with asymmetric pricing effects and we find a significant premium for innovations to the lower-tail factor: high-beta stock... | 66 |
The equation of state for two flavor QCD at N_t=6 | We calculate the two flavor equation of state for QCD on lattices with
lattice spacing a=(6T)^{-1} and find that cutoff effects are substantially
reduced compared to an earlier study using a=(4T)^{-1}. However, it is likely
that significant cutoff effects remain. We fit the lattice data to expected
forms of the free ... | 44 |
Unifying Variational Inference and PAC-Bayes for Supervised Learning
that Scales | Neural Network based controllers hold enormous potential to learn complex,
high-dimensional functions. However, they are prone to overfitting and
unwarranted extrapolations. PAC Bayes is a generalized framework which is more
resistant to overfitting and that yields performance bounds that hold with
arbitrarily high p... | 77 |
The nonlinear electromigration of analytes into confined spaces | We consider the problem of electromigration of a sample ion (analyte) within
a uniform background electrolyte when the confining channel undergoes a sudden
contraction. One example of such a situation arises in microfluidics in the
electrokinetic injection of the analyte into a micro-capillary from a reservoir
of muc... | 55 |
Level-Confluence of 3-CTRSs in Isabelle/HOL | We present an Isabelle/HOL formalization of an earlier result by Suzuki,
Middeldorp, and Ida; namely that a certain class of conditional rewrite systems
is level-confluent. Our formalization is basically along the lines of the
original proof, from which we deviate mostly in the level of detail as well as
concerning s... | 00 |
Pairwise Node Localization From Differences in Their UWB Channels to
Observer Nodes | We consider the problem of localization and distance estimation between a
pair of wireless nodes in a multipath propagation environment, but not the
usual way of processing a channel measurement between them. We propose a novel
paradigm which compares the two nodes' ultra-wideband (UWB) channels to other
nodes, calle... | 22 |
An Interactive Empirical Approach to the Validation of Software Package
Specifications | The objective of this research is the development of a practical system to
manipulate and validate software package specifications. The validation process
developed is based on consistency checks. Furthermore, by means of scenarios,
the customer will be able to interactively experience the specified system
prior to i... | 00 |
Stochastic Neighbor Embedding separates well-separated clusters | Stochastic Neighbor Embedding and its variants are widely used dimensionality
reduction techniques -- despite their popularity, no theoretical results are
known. We prove that the optimal SNE embedding of well-separated clusters from
high dimensions to any Euclidean space R^d manages to successfully separate the
clus... | 77 |
Scalable Meta-Learning with Gaussian Processes | Meta-learning is a powerful approach that exploits historical data to quickly
solve new tasks from the same distribution. In the low-data regime, methods
based on the closed-form posterior of Gaussian processes (GP) together with
Bayesian optimization have achieved high performance. However, these methods
are either ... | 77 |
Assessing Skew Normality in Marks Distribution, a Comparative Analysis
of Shapiro Wilk Tests | This paper investigates the distribution of marks obtained by students across
multiple courses to explore whether the data conforms to a skew-normal
distribution. Traditional methods for assessing normality, such as the Shapiro
Wilk test, often reject normality in datasets with evident skewness. To address
this, we a... | 77 |
Voltage- and temperature-dependent rare-earth dopant contribution to the
interfacial magnetic anisotropy | The control of magnetic materials and devices by voltages without electric
currents holds the promise of power-saving nano-scale devices. Here we study
the temperature-dependent voltage control of the magnetic anisotropy caused by
rare-earth (RE) local moments at an interface between a magnetic metal and a
non-magnet... | 44 |
A Purely Algebraic Justification of the Kabsch-Umeyama Algorithm | The constrained orthogonal Procrustes problem is the least-squares problem
that calls for a rotation matrix that optimally aligns two matrices of the same
order. Over past decades, the algorithm of choice for solving this problem has
been the Kabsch-Umeyama algorithm, which is effectively no more than the
computation... | 33 |
Spatial Bayesian variable selection and grouping for high-dimensional
scalar-on-image regression | Multi-subject functional magnetic resonance imaging (fMRI) data has been
increasingly used to study the population-wide relationship between human brain
activity and individual biological or behavioral traits. A common method is to
regress the scalar individual response on imaging predictors, known as a
scalar-on-ima... | 77 |
Sparse Uniformity Testing | In this paper we consider the uniformity testing problem for high-dimensional
discrete distributions (multinomials) under sparse alternatives. More
precisely, we derive sharp detection thresholds for testing, based on $n$
samples, whether a discrete distribution supported on $d$ elements differs from
the uniform dist... | 33 |
Hybrid Autoregressive Transducer (hat) | This paper proposes and evaluates the hybrid autoregressive transducer (HAT)
model, a time-synchronous encoderdecoder model that preserves the modularity of
conventional automatic speech recognition systems. The HAT model provides a way
to measure the quality of the internal language model that can be used to
decide ... | 22 |
Approximate Sparsity Class and Minimax Estimation | Motivated by the orthogonal series density estimation in $L^2([0,1],\mu)$, in this project we consider a new class of functions that we call the approximate sparsity class. This new class is characterized by the rate of decay of the individual Fourier coefficients for a given orthonormal basis. We establish the $L^2([0... | 11 |
Sharp Analysis for KL-Regularized Contextual Bandits and RLHF | Reverse-Kullback-Leibler (KL) regularization has emerged to be a predominant
technique used to enhance policy optimization in reinforcement learning (RL)
and reinforcement learning from human feedback (RLHF), which forces the learned
policy to stay close to a reference policy. While the effectiveness and
necessity of... | 00 |
Deep Anomaly Detection in Packet Payload | With the widespread adoption of cloud services, especially the extensive
deployment of plenty of Web applications, it is important and challenging to
detect anomalies from the packet payload. For example, the anomalies in the
packet payload can be expressed as a number of specific strings which may cause
attacks. Alt... | 22 |
Deep Learning based Model Predictive Control for Compression Ignition
Engines | Machine learning (ML) and a nonlinear model predictive controller (NMPC) are
used in this paper to minimize the emissions and fuel consumption of a
compression ignition engine. In this work machine learning is applied in two
methods. In the first application, ML is used to identify a model for
implementation in model... | 22 |
Explaining Deep Learning for ECG Analysis: Building Blocks for Auditing
and Knowledge Discovery | Deep neural networks have become increasingly popular for analyzing ECG data
because of their ability to accurately identify cardiac conditions and hidden
clinical factors. However, the lack of transparency due to the black box nature
of these models is a common concern. To address this issue, explainable AI
(XAI) me... | 22 |
Lamina-specific neuronal properties promote robust, stable signal
propagation in feedforward networks | Feedforward networks (FFN) are ubiquitous structures in neural systems and
have been studied to understand mechanisms of reliable signal and information
transmission. In many FFNs, neurons in one layer have intrinsic properties that
are distinct from those in their pre-/postsynaptic layers, but how this affects
netwo... | 55 |
The economic alignment problem of artificial intelligence | Artificial intelligence (AI) is advancing exponentially and is likely to have profound impacts on human wellbeing, social equity, and environmental sustainability. Here we argue that the "alignment problem" in AI research is also an economic alignment problem, as developing advanced AI inside a growth-based system is l... | 11 |
Multilevel Monte Carlo For Exponential L\'{e}vy Models | We apply multilevel Monte Carlo for option pricing problems using exponential
L\'{e}vy models with a uniform timestep discretisation to monitor the running
maximum required for lookback and barrier options. The numerical results
demonstrate the computational efficiency of this approach. We derive estimates
of the con... | 66 |
A microscopic derivation of the quantum measurement postulates | In the mid-19th century, both the laws of mechanics and thermodynamics were
known, and both appeared fundamental. This was changed by Boltzmann and Gibbs,
who showed that thermodynamics can be *derived*, by applying mechanics to very
large systems, and making simple statistical assumptions about their behavior.
Simil... | 44 |
Galaxy evolution across environments as probed by the ages, stellar
metallicities and [alpha/Fe] of central and satellite galaxies | We explore how the star formation and metal enrichment histories of
present-day galaxies have been affected by environment combining stellar
population parameter estimates and group environment characterization for SDSS
DR7. We compare stellar ages, stellar metallicities and element abundance
ratios [alpha/Fe] of sat... | 44 |
A Self-Regulated and Reconfigurable CMOS Physically Unclonable Function
Featuring Zero-Overhead Stabilization | This article presents a reconfigurable physically unclonable function (PUF)
design fabricated using 65-nm CMOS technology. A subthreshold-inverter-based
static PUF cell achieves 0.3% native bit error rate (BER) at 0.062-fJ per bit
core energy efficiency. A flexible, native transistor-based voltage regulation
scheme a... | 22 |
Bounds on an effective thermalization beyond the Zeno limit | Developing protocols for preserving information in quantum systems is a
central quest for implementing realistic quantum computation. In this regard,
the quantum Zeno effect has emerged as a widely utilized technique to safeguard
classical information stored in quantum systems. However, existing results
pertaining to... | 44 |
The looping probability of random heteropolymers helps to understand the
scaling properties of biopolymers | Random heteropolymers are a minimal description of biopolymers and can
provide a theoretical framework to the investigate the formation of loops in
biophysical experiments. A two--state model provides a consistent and robust
way to study the scaling properties of loop formation in polymers of the size
of typical biol... | 55 |
Context-Aware Neural Video Compression on Solar Dynamics Observatory | NASA's Solar Dynamics Observatory (SDO) mission collects large data volumes
of the Sun's daily activity. Data compression is crucial for space missions to
reduce data storage and video bandwidth requirements by eliminating
redundancies in the data. In this paper, we present a novel neural
Transformer-based video comp... | 22 |
Note on log-periodic description of 2008 financial crash | We analyze the financial crash in 2008 for different financial markets from
the point of view of log-periodic function model. In particular, we consider
Dow Jones index, DAX index and Hang Seng index. We shortly discuss the possible
relation of the theory of critical phenomena in physics to financial markets.
| 66 |
Almost harmonic Maass forms and Kac-Wakimoto characters | We resolve a question of Kac, and explain the automorphic properties of
characters due to Kac-Wakimoto pertaining to sl(m|n)^ highest weight modules,
for n \geq 1. We prove that the Kac-Wakimoto characters are essentially
holomorphic parts of certain generalizations of harmonic weak Maass forms which
we call "almost ... | 33 |
Steganography GAN: Cracking Steganography with Cycle Generative
Adversarial Networks | For as long as humans have participated in the act of communication,
concealing information in those communicative mediums has manifested into an
art of its own. Crytographic messages, through written language or images, are
a means of concealment, usually reserved for highly sensitive or compromising
information. Sp... | 00 |
Spectral bounds for the $k$-independence number of a graph | In this paper, we obtain two spectral upper bounds for the $k$-independence
number of a graph which is is the maximum size of a set of vertices at pairwise
distance greater than $k$. We construct graphs that attain equality for our
first bound and show that our second bound compares favorably to previous
bounds on th... | 33 |
Insights on the dip of fault zones in Southern California from modeling
of seismicity with anisotropic point processes | Accurate models of fault zone geometry are important for scientific and
hazard applications. While seismicity can provide high-resolution point
measurements of fault geometry, extrapolating these measurements to volumes may
involve making strong assumptions. This is particularly problematic in
distributed fault zones... | 44 |
The Effect of Punishment and Reward on Cooperation in a Prisoners' Dilemma Game | This paper characterizes how different incentive instruments shape cooperation in a repeated Prisoner`s Dilemma with a continuum of players. A simple tit-for-tat strategy competes against unconditional defection, and the long-run outcome is summarized by a tipping-point share of cooperators, above which cooperation spr... | 11 |
Data variation-aware medical image segmentation | Deep learning algorithms have become the golden standard for segmentation of
medical imaging data. In most works, the variability and heterogeneity of real
clinical data is acknowledged to still be a problem. One way to automatically
overcome this is to capture and exploit this variation explicitly. Here, we
propose ... | 22 |
Joint Bandwidth Allocation and Path Selection in WANs with Path
Cardinality Constraints | In this paper, we study a joint bandwidth allocation and path selection
problem via solving a multi-objective minimization problem under the path
cardinality constraints, namely MOPC. Our problem formulation captures various
types of objectives including the proportional fairness, the total completion
time, as well a... | 22 |
NEWTON: Are Large Language Models Capable of Physical Reasoning? | Large Language Models (LLMs), through their contextualized representations,
have been empirically proven to encapsulate syntactic, semantic, word sense,
and common-sense knowledge. However, there has been limited exploration of
their physical reasoning abilities, specifically concerning the crucial
attributes for com... | 00 |
Generalizations of Kaplansky Theorem Related to Linear Operators | The purpose of this paper is to generalize a very famous result on products
of normal operators, due to I. Kaplansky. The context of generalization is that
of bounded hyponormal and unbounded normal operators on complex separable
Hilbert spaces. Some examples "spice up" the paper.
| 33 |
Emergent quantum mechanics of finances | This paper is an attempt at understanding the quantum-like dynamics of
financial markets in terms of non-differentiable price-time continuum having
fractal properties. The main steps of this development are the statistical
scaling, the non-differentiability hypothesis, and the equations of motion
entailed by this hyp... | 66 |
Mitigating Memorization In Language Models | Language models (LMs) can "memorize" information, i.e., encode training data
in their weights in such a way that inference-time queries can lead to verbatim
regurgitation of that data. This ability to extract training data can be
problematic, for example, when data are private or sensitive. In this work, we
investiga... | 00 |
Active Learning of Dynamics Using Prior Domain Knowledge in the Sampling
Process | We present an active learning algorithm for learning dynamics that leverages
side information by explicitly incorporating prior domain knowledge into the
sampling process. Our proposed algorithm guides the exploration toward regions
that demonstrate high empirical discrepancy between the observed data and an
imperfec... | 22 |
Pricing without no-arbitrage condition in discrete time | In a discrete time setting, we study the central problem of giving a fair
price to some financial product. For several decades, the no-arbitrage
conditions and the martingale measures have played a major role for solving
this problem. We propose a new approach for estimating the super-replication
cost based on convex... | 66 |
Two-Time Correlations for Probing the Aging Dynamics of Jammed Colloids | We present results for the aging dynamics of a jammed 2D colloidal system
obtained with molecular dynamics simulations. We performed extensive
simulations to gather detailed statistics about rare rearrangement events. With
a simple criterion for identifying irreversible events based on Voronoi
tessellations, we find ... | 44 |
DomainCQA: Crafting Knowledge-Intensive QA from Domain-Specific Charts | Chart Question Answering (CQA) evaluates Multimodal Large Language Models (MLLMs) on visual understanding and reasoning over chart data. However, existing benchmarks mostly test surface-level parsing, such as reading labels and legends, while overlooking deeper scientific reasoning. We propose DomainCQA, a framework fo... | 00 |
LQR through the Lens of First Order Methods: Discrete-time Case | We consider the Linear-Quadratic-Regulator (LQR) problem in terms of
optimizing a real-valued matrix function over the set of feedback gains. Such a
setup facilitates examining the implications of a natural initial-state
independent formulation of LQR in designing first order algorithms. It is shown
that this cost fu... | 22 |
Stability of convective rolls in a horizontal layer rotating about an
inclined axis | We present three results on stability of rolls in Boussinesq convection in a
plane horizontal layer with rigid boundaries that is rotating about an inclined
axis with the angular velocity $\Omega=(\Omega_1,\Omega_2,\Omega_3)$. i. We
call the full problem the set of equations governing the temporal behaviour of
the fl... | 44 |
Bayesian Meta-Analysis with Application in Dental Studies | Dental caries remain a persistent global health challenge, and fluoride varnish is widely used as a preventive intervention. This study synthesizes evidence from multiple clinical trials to evaluate the effectiveness of fluoride varnish in reducing Decayed-Missing-Filled (DMF) surfaces. The principal measure of efficac... | 77 |
Lights Out On Nearly Complete Graphs | We study the generalization of the game Lights Out in which the standard square grid board is replaced by a graph. We examine the probability that, when a graph is chosen uniformly at random from the set of graphs with $n$ vertices and $e$ edges, the resulting game of Lights Out is universally solvable. Our work focuse... | 33 |
Persistent Gaps, Partial Gains: A Population-Level Study of COVID-19 Learning Inequalities in the Netherlands | The COVID-19 pandemic disrupted schooling worldwide, raising concerns about widening educational inequalities. Using population-level administrative data from the Netherlands (N = 1,471,217), this study examines how socio-economic disparities in secondary school performance evolved before, during, and after pandemic-re... | 11 |
On stable compactification with Casimir-like potential | Multidimensional cosmological models with a higher dimensional space-time
manifold are investigated under dimensional reduction. In the Einstein
conformal frame, the effective potential for the internal scale factors is
obtained. The stable compactification of the internal spaces is achieved due to
the Casimir effect... | 44 |
Improving the Johnson-Lindenstrauss Lemma | The Johnson-Lindenstrauss Lemma allows for the projection of $n$ points in
$p-$dimensional Euclidean space onto a $k-$dimensional Euclidean space, with $k
\ge \frac{24\ln \emph{n}}{3\epsilon^2-2\epsilon^3}$, so that the pairwise
distances are preserved within a factor of $1\pm\epsilon$. Here, working
directly with th... | 77 |
Astrocytic Ion Dynamics: Implications for Potassium Buffering and Liquid
Flow | We review modeling of astrocyte ion dynamics with a specific focus on the
implications of so-called spatial potassium buffering, where excess potassium
in the extracellular space (ECS) is transported away to prevent pathological
neural spiking. The recently introduced Kirchoff-Nernst-Planck (KNP) scheme for
modeling ... | 55 |
Current density, current-density pathways and molecular aromaticity | Current densities are induced in the electronic structure of molecules when
they are exposed to external magnetic fields. Aromatic molecular rings sustain
net diatropic ring currents, whereas the net ring current in antiaromatic
molecular rings is paratropic and flows in the opposite, non-classical
direction. We pres... | 44 |
Surveying Uncertainty Representation: A Unified Model for Cyber-Physical
Systems | Cyber-Physical Systems (CPS) operate in dynamic environments, leading to
different types of uncertainty. This work provides a comprehensive review of
uncertainty representations and categorizes them based on the dimensions used
to represent uncertainty. Through this categorization, key gaps and limitations
in existin... | 22 |
Model Pairing Using Embedding Translation for Backdoor Attack Detection
on Open-Set Classification Tasks | Backdoor attacks allow an attacker to embed a specific vulnerability in a
machine learning algorithm, activated when an attacker-chosen pattern is
presented, causing a specific misprediction. The need to identify backdoors in
biometric scenarios has led us to propose a novel technique with different
trade-offs. In th... | 00 |
Fast Hybrid Schemes for Fractional Riccati Equations (Rough is not so
Tough) | We solve a family of fractional Riccati differential equations with constant
(possibly complex) coefficients. These equations arise, e.g., in fractional
Heston stochastic volatility models, that have received great attention in the
recent financial literature thanks to their ability to reproduce a rough
volatility be... | 66 |
The interplay of extinction and synchrony in the dynamics of
metapopulation formation | The idea of a metapopulation has become canonical in ecology. Its original
mean field form provides the important intuition that migration and extinction
interact to determine the dynamics of a population composed of subpopulations.
From its conception, it has been evident that the very essence of the
metapopulation ... | 55 |
Controllable Distortion-Perception Tradeoff Through Latent Diffusion for
Neural Image Compression | Neural image compression often faces a challenging trade-off among rate,
distortion and perception. While most existing methods typically focus on
either achieving high pixel-level fidelity or optimizing for perceptual
metrics, we propose a novel approach that simultaneously addresses both aspects
for a fixed neural ... | 22 |
Data Contamination Calibration for Black-box LLMs | The rapid advancements of Large Language Models (LLMs) tightly associate with
the expansion of the training data size. However, the unchecked
ultra-large-scale training sets introduce a series of potential risks like data
contamination, i.e. the benchmark data is used for training. In this work, we
propose a holistic... | 00 |
CaseCohortCoxSurvival: an R Package for Case-Cohort Inference for
Relative Hazard and Pure Risk under the Cox Model | The case-cohort design allows analysis of multiple endpoints and only
requires covariates to be measured for cases and non-cases in a random
subcohort from the cohort. Stratification of subcohort sampling and weight
calibration increase efficiency of estimates of log-relative hazards and
covariate-specific pure risk,... | 77 |
The Impact of Acquisition on Product Quality in the Console Gaming
Industry | The console gaming industry, a dominant force in the global entertainment
sector, has witnessed a wave of consolidation in recent years, epitomized by
Microsoft's high-profile acquisitions of Activision Blizzard and Zenimax. This
study investigates the repercussions of such mergers on consumer welfare and
innovation ... | 11 |
Validation and traceability of miniaturized multi-parameter cluster of
radiosondes used for atmospheric observations | In this work we designed and developed a cluster of light expendable
radiosondes that can float passively inside warm clouds to study their
micro-physical processes. This involves the tracking of both saturated and
unsaturated turbulent air parcels. The aim of this new kind of observation
system is to obtain Lagrangi... | 22 |
Interplay between intraspecific suppression and environment in shaping biodiversity | Understanding the mechanisms that sustain high biodiversity remains a central challenge. MacArthur's classical consumer-resource model (MCRM) suggests that consumer diversity is limited by the number of available resources, yet empirical observations often exceed this bound. To address this, we extend the generalized c... | 55 |
Inference of the Dynamic Aging-related Biological Subnetwork via Network
Propagation | Gene expression (GE) data capture valuable condition-specific information
("condition" can mean a biological process, disease stage, age, patient, etc.)
However, GE analyses ignore physical interactions between gene products, i.e.,
proteins. Since proteins function by interacting with each other, and since
biological... | 55 |
The number of graphs of given diameter | In this paper it is proved that there are constants 0< c_2< c_1 such that an
asymptotic formula can be given for the the number of (labeled) n-vertex graphs
of diameter d whenever n tends to infinity and 2 < d < n - c_1 (log n). A
typical graph of diameter d consists of a combination of an induced path of
length d an... | 33 |
Enhancing Consistency and Mitigating Bias: A Data Replay Approach for
Incremental Learning | Deep learning systems are prone to catastrophic forgetting when learning from
a sequence of tasks, as old data from previous tasks is unavailable when
learning a new task. To address this, some methods propose replaying data from
previous tasks during new task learning, typically using extra memory to store
replay da... | 00 |
VEPerform: a web resource for evaluating the performance of variant
effect predictors | Computational variant effect predictors (VEPs) are providing increasingly
strong evidence to classify the pathogenicity of missense variants. Precision
vs. recall analysis is useful in evaluating VEP performance, especially when
adjusted for imbalanced test sets. Here, we describe VEPerform, a web-based
tool for eval... | 55 |
Semiparametrically Point-Optimal Hybrid Rank Tests for Unit Roots | We propose a new class of unit root tests that exploits invariance properties
in the Locally Asymptotically Brownian Functional limit experiment associated
to the unit root model. The invariance structures naturally suggest tests that
are based on the ranks of the increments of the observations, their average,
and an... | 11 |
HOLISMOKES -- VII. Time-delay measurement of strongly lensed Type Ia
supernovae using machine learning | The Hubble constant ($H_0$) is one of the fundamental parameters in
cosmology, but there is a heated debate around the $>$4$\sigma$ tension between
the local Cepheid distance ladder and the early Universe measurements. Strongly
lensed Type Ia supernovae (LSNe Ia) are an independent and direct way to
measure $H_0$, wh... | 44 |
Classifications of Single-input Lower Triangular Forms | The purposes of this paper are to classify lower triangular forms and to
determine under what conditions a nonlinear system is equivalent to a specific
type of lower triangular forms. According to the least multi-indices and the
greatest essential multi-index sets, which are introduced as new notions and
can be obtai... | 22 |
Self-Learned Kernel Low Rank Approach TO Accelerated High Resolution 3D
Diffusion MRI | Diffusion Magnetic Resonance Imaging (dMRI) is a promising method to analyze
the subtle changes in the tissue structure. However, the lengthy acquisition
time is a major limitation in the clinical application of dMRI. Different image
acquisition techniques such as parallel imaging, compressed sensing, has
shortened t... | 22 |
Godbillon-Vey type functional for almost contact manifolds | Many contact metric manifolds are critical points of curvature functionals
restricted to spaces of associated metrics. The Godbillon-Vey functional has
never been considered in a variational context in contact geometry. Recently we
extended this functional from foliations to arbitrary plane fields on a
3-dimensional ... | 33 |
Temporal Link Prediction in Social Networks Based on Agent Behavior
Synchrony and a Cognitive Mechanism | Temporality, a crucial characteristic in the formation of social
relationships, was used to quantify the long-term time effects of networks for
link prediction models, ignoring the heterogeneity of time effects on different
time scales. In this work, we propose a novel approach to link prediction in
temporal networks... | 00 |
Unsupervised Speaker Adaptation using Attention-based Speaker Memory for
End-to-End ASR | We propose an unsupervised speaker adaptation method inspired by the neural
Turing machine for end-to-end (E2E) automatic speech recognition (ASR). The
proposed model contains a memory block that holds speaker i-vectors extracted
from the training data and reads relevant i-vectors from the memory through an
attention... | 22 |
EEEA-Net: An Early Exit Evolutionary Neural Architecture Search | The goals of this research were to search for Convolutional Neural Network
(CNN) architectures, suitable for an on-device processor with limited computing
resources, performing at substantially lower Network Architecture Search (NAS)
costs. A new algorithm entitled an Early Exit Population Initialisation (EE-PI)
for ... | 00 |
Cluster-Level Experiments using Temporal Switchback Designs: Precision Gains in Pricing A/B Tests at LATAM Airlines | Experimentation is central to modern digital businesses, but many operational decisions cannot be randomized at the user level. In such cases, cluster-level experiments, where clusters are usually geographic, come to the rescue. However, such experiments often suffer from low power due to persistent cluster heterogenei... | 77 |
On the canonical degrees of Gorenstein threefolds of general type | Let $X$ be a Gorenstein minimal projective $3$-fold with at worst locally
factorial terminal singularities. Suppose that the canonical map is generically
finite onto its image. C. Hacon showed that the canonical degree is universally
bounded by $576$. We improved Hacon's universal bound to $360$. Moreover, we
gave al... | 33 |
Automorphisms of del Pezzo surfaces in characteristic 2 | We classify the automorphism groups of del Pezzo surfaces of degrees one and
two over an algebraically closed field of characteristic two. This finishes the
classification of automorphism groups of del Pezzo surfaces in all
characteristics.
| 33 |
Electrified Autonomous Freight Benefit analysis on Fleet, Infrastructure
and Grid Leveraging Grid-Electrified Mobility (GEM) Model | This paper analyzes the potential benefit of heavy-duty vehicle (HDV)
electrification and automation on fleet cost, infrastructure cost, grid, and
environmental impact. In this work, we extended the vehicle electrification
benefit analysis tool: Grid-Electrified Mobility (GEM) model, which had
primarily been used to ... | 22 |
What the odor is not: Estimation by elimination | Olfactory systems use a small number of broadly sensitive receptors to
combinatorially encode a vast number of odors. We propose a method of decoding
such distributed representations by exploiting a statistical fact: receptors
that do not respond to an odor carry more information than receptors that do
because they s... | 55 |
Irreversibility of the Renormalization Group Flow in Two Dimensional
Quantum Gravity | We argue that the torus partition sum in $2d$ (super) gravity, which counts
physical states in the theory, is a decreasing function of the renormalization
group scale. As an application we chart the space of $(\hat c\leq1)$ $c\leq1$
models coupled to (super) gravity, confirming and extending ideas due to A.
Zamolodch... | 44 |
Statistical Phylogenetic Tree Analysis Using Differences of Means | We propose a statistical method to test whether two phylogenetic trees with
given alignments are significantly incongruent. Our method compares the two
distributions of phylogenetic trees given by the input alignments, instead of
comparing point estimations of trees. This statistical approach can be applied
to gene t... | 55 |
Inland waterway transport accident analysis of Bangladesh: based on
location, time, and regression approach | Bangladesh, situated in the foothills of the Himalayas in South Asia, is a
nation characterized by its extensive river network. This riverine state
comprises various features such as small hill ranges, meandering seasonal
creeks, muddy canals, picturesque rivers, their tributaries, and branching
streams. Numerous cit... | 77 |
ICT Intervention in the Containment of the Pandemic Spread of COVID-19:
An Exploratory Study | The objective of this article is to explore the Information and Communication
Technology (ICT) interventions and its strengths, weaknesses, opportunities and
threats for the containment of the pandemic spread of novel Coronavirus. The
research adopted a qualitative research approach, while the study data were
collect... | 00 |
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