Neural Network

Neural networks are computational models inspired by the structure and function of the brain, primarily aimed at approximating complex functions and solving diverse problems through learning from data. Current research emphasizes improving efficiency and robustness, exploring novel architectures like sinusoidal neural fields and hybrid models combining neural networks with radial basis functions, as well as developing methods for understanding and manipulating the internal representations learned by these networks, such as through hyper-representations of network weights. These advancements are driving progress in various fields, including computer vision, natural language processing, and scientific modeling, by enabling more accurate, efficient, and interpretable AI systems.

3917papers

Papers - Page 5

March 13, 2025

Ecological Neural Architecture Search
Evolutionary Algorithm Fitness Approximation Neural Architecture Search Neural Network
Evaluating a Novel Neuroevolution and Neural Architecture Search System
Neural Network Large Transformer Model Neural Architecture Search Standard Deep
Efficient Reachability Analysis for Convolutional Neural Networks Using Hybrid Zonotopes
Convolutional Neural Network Set Based Polynomial Zonotopes Neural Network Reachable Set Reachability Analysis
Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks
Explainable Deep Learning Neural Network Bayesian Neural Network Predictive Uncertainty Latent Variable
Langevin Monte-Carlo Provably Learns Depth Two Neural Nets at Any Size and Data
R\'enyi Divergence Large Depth Neural Network Langevin Monte Carlo Loss Function Size Matter Raw Data
Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding
Language Model Speculative Exploration Token Generation Neural Network Accurate Decoding Hybrid Framework Generation Model
RSR-NF: Neural Field Regularization by Static Restoration Priors for Dynamic Imaging
Neural Network Dynamic Imaging Neural Field Temporal Regularization Deep Image
Adaptive Moment Estimation Optimization Algorithm Using Projection Gradient for Deep Learning
Neural Network Second Order Moment Projection Bias Adaptive Moment Estimation Deep Learning Adam Optimizer Natural Gradient
Thermodynamic Bound on Energy and Negentropy Costs of Inference in Deep Neural Networks
Energy Efficient AI Energy Policy Research Energy Cost Hidden CoST Scientific Inference Energy Constraint Energy Efficient Inference Neural Network

March 12, 2025

Predicting Tropical Cyclone Track Forecast Errors using a Probabilistic Neural Network
Tropical Cyclone Neural Network Tropical Cyclone Intensity Track Reconstruction Better Uncertainty Estimation Probabilistic Model
Learning richness modulates equality reasoning in neural networks
Perceptual Understanding Neural Network Task Specific Representation
Parsing the Language of Expression: Enhancing Symbolic Regression with Domain-Aware Symbolic Priors
Expression Generation Symbolic Learning Symbolic Regression Neural Network Recurrent Neural Network Human Expression Human Language
Global Convergence and Rich Feature Learning in L-Layer Infinite-Width Neural Networks under μP Parametrization
Neural Network Deep Representation Global Convergence Stochastic Gradient Descent Deep Neural Network Feature Learning Neural Tangent Kernel
Neural Network-Based Change Point Detection for Large-Scale Time-Evolving Data
Neural Network Change Point Signal Processing Change Point Detection Neural Topic
Mapping fMRI Signal and Image Stimuli in an Artificial Neural Network Latent Space: Bringing Artificial and Natural Minds Together
Human Mind Neural Network Visual Stimulus Latent Space Representation Functional Magnetic Resonance Imaging Latent Space Representational Similarity
Constraint-Guided Learning of Data-driven Health Indicator Models: An Application on the Pronostia Bearing Dataset
Constrained Problem Application Proficiency State of Health Constrained Gradient Neural Network Self Consistent Constraint Constraint Learning
Self-Consistent Equation-guided Neural Networks for Censored Time-to-Event Data
Neural Network Proportional Hazard Self Consistency Time to Event Data Survival Function
Quantitative Analysis of Deeply Quantized Tiny Neural Networks Robust to Adversarial Attacks
Adversarial Attack White Box Adversarial Attack DNN Architecture Neural Network Quantitative Analysis

March 11, 2025

Neural Learning Rules from Associative Networks Theory
Neural Network Learning Rule Associative Memory Associative Recall Neural Dynamic
HERO: Human Reaction Generation from Videos
Interactive AI Human Reaction Gameplay Video Neural Network

Neural Network

Papers - Page 5

Ecological Neural Architecture Search

Evaluating a Novel Neuroevolution and Neural Architecture Search System

Efficient Reachability Analysis for Convolutional Neural Networks Using Hybrid Zonotopes

Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks

Langevin Monte-Carlo Provably Learns Depth Two Neural Nets at Any Size and Data

Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding

RSR-NF: Neural Field Regularization by Static Restoration Priors for Dynamic Imaging

Adaptive Moment Estimation Optimization Algorithm Using Projection Gradient for Deep Learning

Thermodynamic Bound on Energy and Negentropy Costs of Inference in Deep Neural Networks

Predicting Tropical Cyclone Track Forecast Errors using a Probabilistic Neural Network

Learning richness modulates equality reasoning in neural networks

Parsing the Language of Expression: Enhancing Symbolic Regression with Domain-Aware Symbolic Priors

Global Convergence and Rich Feature Learning in L-Layer Infinite-Width Neural Networks under μP Parametrization

Neural Network-Based Change Point Detection for Large-Scale Time-Evolving Data

Mapping fMRI Signal and Image Stimuli in an Artificial Neural Network Latent Space: Bringing Artificial and Natural Minds Together

Constraint-Guided Learning of Data-driven Health Indicator Models: An Application on the Pronostia Bearing Dataset

Self-Consistent Equation-guided Neural Networks for Censored Time-to-Event Data

Quantitative Analysis of Deeply Quantized Tiny Neural Networks Robust to Adversarial Attacks

Neural Learning Rules from Associative Networks Theory

HERO: Human Reaction Generation from Videos