Neural Network

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Period ending 2026-09-21

28 new papers

A weekly snapshot of new work published in Neural Network.

Period ending 2026-09-14

26 new papers

A weekly snapshot of new work published in Neural Network.

Period ending 2026-09-07

27 new papers

A weekly snapshot of new work published in Neural Network.

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1,083 papers

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  1. PAWN: Piece Value Analysis with Neural Networks

    Apr 16, 2026Ethan Tang, Hasan Davulcu, Jia Zou +1ValueNeural Network

  2. ProtoTTA: Prototype-Guided Test-Time Adaptation

    Apr 16, 2026Mohammad Mahdi Abootorabi, Parvin Mousavi, Purang Abolmaesumi +1Learnable PrototypesTraining-Free Inference Framework

  3. A Nonlinear Separation Principle via Contraction Theory: Applications to Neural Networks, Control, and Learning

    Apr 16, 2026Anand Gokhale, Anton V. Proskurnikov, Yu Kawano +1Neural ControlNeural Network

  4. Low-Cost System for Automatic Recognition of Driving Pattern in Assessing Interurban Mobility using Geo-Information

    Apr 16, 2026Oscar Romero, Aika Silveira Miura, Lorena Parra +1DrivingLane Geometry

  5. KVNN: Learnable Multi-Kernel Volterra Neural Networks

    Apr 16, 2026Haoyu Yun, Hamid Krim, Yufang BaoNeural Tangent KernelNeural Network

  6. Beyond the Laplacian: Doubly Stochastic Matrices for Graph Neural Networks

    Apr 16, 2026Zhaobo Hu, Vincent Gauthier, Mehdi NaimaGraph Neural NetworksGraph Laplacians

  7. Improving Sparse Autoencoder with Dynamic Attention

    Apr 16, 2026Dongsheng Wang, Jinsen Zhang, Dawei Su +1Improving Sparse AutoencodersDynamic Sparse Attention

  8. Python library supporting Discrete Variational Formulations and training solutions with Collocation-based Robust Variational Physics Informed Neural Networks (DVF-CRVPINN)

    Apr 16, 2026Tomasz Służalec, Marcin Łoś, Askold Vilkha +1Bayesian QuadratureNeural Network

  9. Foundation Models in Robotics: A Comprehensive Review of Methods, Models, Datasets, Challenges and Future Research Directions

    Apr 16, 2026Aggelos Psiris, Vasileios Argyriou, Evangelos K. Markakis +4Foundation ModelRobotics

  10. Lightweight Geometric Adaptation for Training Physics-Informed Neural Networks

    Apr 16, 2026Kang An, Chenhao Si, Shiqian Ma +1Conventional Physics-Informed Neural NetworksCurvature-Aware Quadratic Banks

  11. Gating Enables Curvature: A Geometric Expressivity Gap in Attention

    Apr 16, 2026Satwik Bathula, Anand A. JoshiCurvatureExpressivity

  12. A Complete Symmetry Classification of Shallow ReLU Networks

    Apr 15, 2026Pranavkrishnan RamakrishnanRectified Linear Unit NetworksSymmetry

  13. MOONSHOT : A Framework for Multi-Objective Pruning of Vision and Large Language Models

    Apr 14, 2026Gabriel Afriat, Xiang Meng, Shibal Ibrahim +2PruningLarge Language Model Compression

  14. Synthesizing real-world distributions from high-dimensional Gaussian Noise with Fully Connected Neural Network

    Apr 10, 2026Joanna KomorniczakSynthetic Tabular DataSynthetic Data

  15. Neural parametric representations for thin-shell shape optimisation

    Apr 8, 2026Xiao Xiao, Fehmi CirakInformation-Geometric OptimizationSuperquadrics

  16. Fine-Tuning Integrity for Modern Neural Networks: Structured Drift Proofs via Norm, Rank, and Sparsity Certificates

    Apr 6, 2026Zhenhang Shang, Yingzhe Yu, Kani ChenFinetuningZero-Knowledge Proofs

  17. Similarity of Neural Network Representations in Superposition

    Mar 31, 2026Sunny Liu, Habon Issa, André Longon +4Implicit Neural RepresentationsLatent Representation Alignment

  18. Working Paper: Towards a Category-theoretic Comparative Framework for Artificial General Intelligence

    Mar 30, 2026Pablo de los Riscos, Fernando J. Corbacho, Michael A. ArbibModular Agentic FrameworkNeural Architectures

  19. The Rules-and-Facts Model for Simultaneous Generalization and Memorization in Neural Networks

    Mar 26, 2026Gabriele Farné, Fabrizio Boncoraglio, Lenka ZdeborováMemorizationSingular Learning Theory

  20. Amortized Inference for Correlated Discrete Choice Models via Equivariant Neural Networks

    Mar 25, 2026Easton Huch, Michael KeaneDiscrete Choice ModelsMaximum Likelihood

  21. Latency Coding for Efficient and Low-Latency Deep Spiking Neural Networks

    Mar 24, 2026Yi Lu, Jianhao Ding, Zhaofei YuSpiking Neural NetworksBinary Spikes

  22. Asymptotic Learning Curves for Diffusion Models with Random Features Score and Manifold Data

    Mar 24, 2026Anand Jerry George, Nicolas MacrisScore-Based Diffusion ModelLow-Dimensional Structure

  23. From Arithmetic to Logic: The Resilience of Logic and Lookup-Based Neural Networks Under Parameter Bit-Flips

    Mar 24, 2026Alan T. L. Bacellar, Sathvik Chemudupati, Shashank Nag +4Neural NetworkNeural Architectures

  24. SDE-Driven Spatio-Temporal Hypergraph Neural Networks for Irregular Longitudinal fMRI Connectome Modeling in Alzheimer's Disease

    Mar 20, 2026Ruiying Chen, Yutong Wang, Houliang Zhou +3AlzheimerNeural Ordinary Differential Equations

  25. WarPGNN: A Parametric Thermal Warpage Analysis Framework with Physics-aware Graph Neural Network

    Mar 19, 2026Haotian Lu, Jincong Lu, Sachin Sachdeva +1Graph Neural NetworksChip Design

  26. Variational Phasor Circuits for Phase-Native Brain-Computer Interface Classification

    Mar 18, 2026Dibakar SigdelBrain-Computer InterfaceNeural Network

  27. Dataset Distillation Efficiently Encodes Low-Dimensional Representations from Gradient-Based Learning of Non-Linear Tasks

    Mar 16, 2026Yuri Kinoshita, Naoki Nishikawa, Taro ToyoizumiLow-Dimensional StructureContext Compression

  28. GP-VM×\timesSMA: Benchmarking General-Purpose Vision Models and Specialized Architectures for 2D Medical Image Segmentation

    Mar 13, 2026Vanessa Borst, Anna Riedmann, Samuel KounevMedical Image SegmentationMedical Imaging

  29. Evidential Perfusion Physics-Informed Neural Networks with Residual Uncertainty Quantification

    Mar 10, 2026Junhyeok Lee, Minseo Choi, Han Jang +5Conventional Physics-Informed Neural NetworksStroke

  30. MUSA-PINN: Multi-scale Weak-form Physics-Informed Neural Networks for Fluid Flow in Complex Geometries

    Mar 9, 2026Weizheng Zhang, Xunjie Xie, Hao Pan +4Conventional Physics-Informed Neural NetworksFluid Dynamics

  31. Lipschitz-Based Robustness Certification Under Floating-Point Execution

    Mar 6, 2026Toby MurrayFloating-PointLipschitz Constant

  32. Enhancing Physics-Informed Neural Networks with Domain-aware Fourier Features: Towards Improved Performance and Interpretable Results

    Mar 3, 2026Alberto Miño Calero, Luis Salamanca, Konstantinos E. TatsisConventional Physics-Informed Neural NetworksNeural Network

  33. To Use or not to Use Muon: How Simplicity Bias in Optimizers Matters

    Feb 28, 2026Sara Dragutinović, Yedi Zhang, Rajesh RanganathMuon OptimizerMuon

  34. Causal Mechanism Reduction: Mechanism Replacement for Neural Network Pruning and Abstraction

    Feb 27, 2026Amir AsiaeeAblationRectified Linear Unit Networks

  35. Generating adversarial inputs for a graph neural network model of AC power flow

    Feb 20, 2026Robert ParkerAc Optimal Power FlowNeural Network Verification

  36. StackingNet: Collective Inference Across Independent AI Foundation Models

    Feb 14, 2026Siyang Li, Chenhao Liu, Dongrui Wu +2Wireless Foundation ModelsArtificial Intelligence Models

  37. Learning functional components of PDEs from data using neural networks

    Feb 13, 2026Torkel E. Loman, Yurij Salmaniw, Antonio Leon Villares +2Partial Differential EquationsNeural-Network Approximation

  38. Rational Neural Networks have Expressivity Advantages

    Feb 12, 2026Maosen Tang, Alex TownsendActivation FunctionsNeural Network

  39. Efficient reduction of stellar contamination and noise in planetary transmission spectra using neural networks

    Feb 10, 2026David S. Duque-Castaño, Lauren Flor-Torres, Jorge I. ZuluagaExoplanet AtmospheresAtmospheric Dynamics

  40. CauScale: Neural Causal Discovery at Scale

    Feb 9, 2026Bo Peng, Sirui Chen, Jiaguo Tian +2Causal Foundation ModelsCausal Reasoning

  41. Entropy-Generated Attention Beyond Softmax and Entmax: Kaniadakis and Reciprocal-Symmetric Abe Operators

    Feb 9, 2026Gunn KimEntropy-Regularized Equilibrium SelectionGumbel-Softmax Relaxation

  42. Perturbing the Phase: Analyzing Adversarial Robustness of Complex-Valued Neural Networks

    Feb 6, 2026Florian Eilers, Christof Duhme, Xiaoyi JiangNeural Network VerificationNeural Network

  43. Revisiting the Shape Convention of Transformer Language Models

    Feb 6, 2026Feng-Ting Liao, Guan-Ting Yi, Tzu-Quan Lin +2Transformer ArchitecturesNeural Architectures

  44. Geometry-Preserving Neural Architectures on Manifolds with Boundary

    Feb 3, 2026Karthik Elamvazhuthi, Shiba Biswal, Kian Rosenblum +4ManifoldsRepresentational Geometry

  45. Deep networks learn to parse uniform-depth context-free languages from local statistics

    Jan 31, 2026Jack T. Parley, Francesco Cagnetta, Matthieu WyartContext-Free GrammarsDeep Network

  46. Complete Identification of Deep ReLU Networks through Łukasiewicz Logic

    Jan 30, 2026Yani Zhang, Helmut BölcskeiRectified Linear Unit NetworksPropositions

  47. Provable Learning of Random Hierarchy Models and Hierarchical Shallow-to-Deep Chaining

    Jan 27, 2026Yunwei Ren, Yatin Dandi, Florent Krzakala +1Deep NetworkSearch Depth

  48. Neural Particle Automata: Learning Self-Organizing Particle Dynamics

    Jan 22, 2026Hyunsoo Kim, Ehsan Pajouheshgar, Sabine Süsstrunk +2Neural Cellular AutomataPhysical Dynamics

  49. Linearized subspace refinement framework to expose hidden accuracy in trained neural networks

    Jan 20, 2026Wenbo Cao, Weiwei ZhangLeast SquaresNeural Network

  50. Graph Neural Networks are Heuristics

    Jan 19, 2026Yimeng Min, Carla P. GomesGraph Neural NetworksCombinatorial Optimization

  51. Adaptively trained Physics-informed Radial Basis Function Neural Networks for Solving Multi-asset Option Pricing Problems

    Jan 19, 2026Yan Ma, Yumeng Ren, Elisabeth LarssonDerivative PricingConventional Physics-Informed Neural Networks

  52. Neural Architectures for Amortized Bayesian Inference: Statistical Foundations and Empirical Assessments

    Jan 12, 2026Roy Shivam Ram Shreshtth, Arnab Hazra, Gourab MukherjeeBayesian Neural NetworksBayesian

  53. FlexAct: Why Learn when you can Pick?

    Jan 10, 2026Ramnath Kumar, Kyle Ritscher, Junmin Judy +2Activation FunctionsGumbel-Softmax Relaxation

  54. AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages

    Jan 10, 2026Hao Yu, Tianyi Xu, Michael A. Hedderich +3Large Language Model PretrainingAfrican Languages

  55. Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning

    Jan 1, 2026Abhisek Ganguly, Santosh Ansumali, Sauro SucciConventional Physics-Informed Neural NetworksNeural Partial Differential Equation Solvers

  56. Quantitative Understanding of PDF Fits and their Uncertainties

    Dec 30, 2025Amedeo Chiefa, Luigi Del Debbio, Richard KenwayHigh Energy PhysicsNeural Tangent Kernel

  57. KernelEvolve: Scaling Agentic Kernel Coding for Heterogeneous AI Accelerators at Meta

    Dec 29, 2025Gang Liao, Hongsen Qin, Ying Wang +36AcceleratorLarge-Scale Recommendation Systems

  58. Learnability Window in Gated Recurrent Neural Networks

    Dec 5, 2025Lorenzo LiviRecurrent Neural NetworksGated Recurrent Unit

  59. Mean-Field Model for Two-Layer Neural Networks Trained with Consensus-Based Optimization

    Nov 26, 2025William De Deyn, Michael Herty, Giovanni SamaeyNeural Network OptimizationTwo-Layer Neural Networks

  60. Pre-train to Gain: Robust Learning Without Clean Labels

    Nov 25, 2025David Szczecina, Nicholas Pellegrino, Paul FieguthNoisy LabelsSelf-Supervised