Neural Network

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Period ending 2026-09-21

28 new papers

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Period ending 2026-09-14

26 new papers

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Period ending 2026-09-07

27 new papers

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  1. Tools to Explain Neural Networks for Power System Dynamics

    Aug 8, 2026Petros Ellinas, Johanna Vorwerk, Spyros ChatzivasileiadisPower SystemsNeural Network

  2. Uncertainty-Aware Ensemble Deep Randomized Neural Networks for Classification

    Aug 7, 2026M. Sajid, A. Quadir, A. Rahaman +2Random ForestEnsemble

  3. QFCQT: A Chaotically Gated Quantformer Framework for Volatile Time-Series Forecasting

    Aug 7, 2026Junkai Lin, Siqi Hou, Raymond LeeChaosStochastic Volatility

  4. PTQ4SNN: Membrane-Aware Post-Training Quantization for Spiking Neural Networks

    Aug 7, 2026Hui Xie, Tong Shi, Haotong Qin +3Spiking Neural NetworksWeight-Only Quantization

  5. Tensor Network Kernel Machines: A JAX Framework for Machine Learning and Nonlinear System Identification

    Aug 7, 2026Albert Saiapin, Kim BatselierTensor NetworksNeural Tangent Kernel

  6. Learning in Deep Networks under Dale's Constraint

    Aug 7, 2026Roy Abel, Shimon UllmanSynaptic PlasticityBackpropagation

  7. Mathematical Principles and Experimental Discoveries of the Emergence of Symbolic Patterns in Artificial Neural Networks

    Aug 7, 2026Quanshi Zhang, Qihan Ren, Siyu LouNeuro-Symbolic FrameworkNeural Network

  8. Cryptanalytic Extraction of Isolated Bias-Free GLU Feed-Forward Blocks by Antipodal Separation

    Aug 6, 2026Chunhui Shi, Xinwen FuRectified Linear Unit NetworksSeparation

  9. Cascading Through the Hierarchy: Regularizer-Induced Feature Detection as Phase Transitions in Deep Linear Neural Networks

    Aug 6, 2026Björn Ladewig, Ibrahim Talha Ersoy, Karoline WiesnerFeature LearningLoss Landscape

  10. Threshold-Based Early Stopping of Accumulations in Neural Networks with Binary Activation

    Aug 6, 2026Quentin Luquet de Saint-Germain, Massil Ait Abdeslam, Jean Pierre DavidEarly StoppingNeural Network

  11. Convergent Evolution in Neural Representation Space: Emergent Order in Deep Belief Networks

    Aug 6, 2026Patrick Krauss, Achim Schilling, Andreas Maier +2Modern Deep NetworksUnsupervised

  12. Alternating Levenberg-Marquardt Training of Physics-Informed Neural Networks with Fourier-Enhanced Features

    Aug 6, 2026Yulun Wu, Matthieu Barreau, Miguel Aguiar +1Conventional Physics-Informed Neural NetworksNewton

  13. An active-learning framework for real-time depth perception from monocular vision streams

    Aug 5, 2026Xiaorong Zeng, Weiqiang Chen, Peng Shi +4Depth EstimationMobilenetv2

  14. The Neural Echo: A Signal Processing Perspective for Understanding Neural Networks

    Aug 5, 2026Chongbiao Wang, Daniel Gaa, Joachim Weickert +1Neural NetworkConvolutional Neural Networks

  15. Continual-Learning Physics-Informed Neural Networks for Parameterized Partial Differential Equations

    Aug 5, 2026Xujia Chen, Xinyue Hu, Letian Chen +2Conventional Physics-Informed Neural NetworksPartial Differential Equations

  16. A Counterexample to Fourier Alignment in Single-Neuron Modular Addition

    Aug 5, 2026Gautam Neelakantan MemanaRectified Linear UnitModular Addition

  17. Understanding Fault Tolerance of Adversarially Robust Pruned Models

    Aug 4, 2026Manali Dangarikar, Cory MerkelModern Deep NetworksHeterogeneous Pruning Scores

  18. A Physics-Flavored Transformer Network for Parametrizing Contraction Dynamics of Engineered Skeletal Muscle Tissues

    Aug 4, 2026Mattias Luber, Timo BetzConventional Physics-Informed Neural NetworksMuscle Anatomy

  19. Tight Worst-Case Bounds for the Smallest Eigenvalue of ReLU NTK Gram Matrices

    Aug 4, 2026Zhao SongLargest EigenvalueRectified Linear Unit

  20. When Should Graph Attention Be Sparse? Learning a Per-Edge Tsallis Index

    Aug 3, 2026Kleyton da Costa, Bernardo ModenesiHeterogeneous Graph TransformersText-Attributed Graph

  21. Contrast-invariant deep ptychography neural networks

    Aug 3, 2026Albert Vong, Steven Henke, Oliver Hoidn +6Equivariant Neural NetworksNeural Network

  22. Neural Networks with Local Converging Inputs for Efficient Options Pricing Models

    Aug 3, 2026Harris Cobb, Wenbo Hao, Yingjie LiuDerivative PricingNeural Network

  23. Constrained Co-Design for Photonic Bayesian Neural Networks

    Aug 3, 2026Hendrik Borras, Xiao Wang, Bernhard Klein +4Bayesian Neural NetworksConventional Physics-Informed Neural Networks

  24. CoRe-GNN: Multilevel Message passing on Coarsened graphs

    Aug 3, 2026Antonin Joly, Nicolas Keriven, Aline RoumyGraph Neural NetworksGnn-Based Detectors

  25. SMM Transformer: Leveraging Spiking Neural Networks for Multimodal Tasks

    Aug 3, 2026Xiubo Liang, Jinxing Han, Yuke Li +3Spiking Neural NetworksMultimodal Transformers

  26. Perception-and-action system for humanoid robot task execution in construction

    Aug 3, 2026Yanxi Liu, Yizhi LiuPerception-Action LoopConstruction

  27. Plasticity of Growing and Elastic Neural Networks in Online Continual Learning

    Aug 2, 2026Jeong Min Kong, Richard S. SuttonPlasticityEfficient Continual Learning

  28. Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View

    Aug 2, 2026Tong Mao, Jinchao XuNeural-Network ApproximationApproximation

  29. Hybrid Quantum Neural Networks: Theory, Implementations, and Applications

    Aug 2, 2026Léo Monbroussou, Maniraman Periyasamy, Viacheslav Kuzmin +4Quantum Neural NetworksHybrid Quantum Neural Networks

  30. Differentiable Lifting for Topological Neural Networks

    Aug 2, 2026Jorge Luiz Franco, Gabriel Duarte, Alexander Nikitin +3Topological Deep LearningGraph Neural Networks

  31. Kilobyte Models: Neural Networks as a Seed and a Quantized Latent

    Aug 1, 2026Sahil Rajesh DhayalkarModel WeightsNeural Network

  32. Adaptive Quantum Physics-Informed Neural Networks for Differential Equations with Applications to Fluid Dynamics

    Aug 1, 2026Fabio Pereira dos Santos, Renato Portugal, Júlio de Castro Vargas Fernandes +1Conventional Physics-Informed Neural NetworksHybrid Quantum Neural Networks

  33. NISF++: Geometrically-grounded implicit representations of 3D+time cardiac function from 2D short- and long-axis MR views

    Aug 1, 2026Nil Stolt-Ansó, Maik Dannecker, Steven Jia +2Cardiac Magnetic Resonance ImagingWhole-Heart Segmentation

  34. Assessing the Generalization of Graph Neural Networks for Fault Location Across Increasing Distributed Energy Resource Penetration Levels

    Jul 31, 2026Burak Karabulut, Olayiwola Arowolo, Carlo Manna +2Temporal Graph Neural NetworksGraph Neural Networks

  35. Learning Lookahead Lemmas for Neural Network Verification

    Jul 31, 2026Liam Davis, Haoze WuNeural Network VerificationNeural Network

  36. Extrapolating the emergence of Hamiltonian chaos with random-feature Hamiltonian neural networks

    Jul 31, 2026Jaesung ChoiHamiltonianNeural Network

  37. Mining Verdict Boundaries for Neural Network Verification

    Jul 31, 2026Jiawei Ren, Guanqin Zhang, Zhenya Zhang +1Neural Network VerificationUpper Bounds

  38. Latent Lie-Poisson Neural Networks (LLPNNs): Discovering the motion of Lie-Poisson systems through observable data and latent dynamics

    Jul 31, 2026Vakhtang PutkaradzeLatent DynamicsHamiltonian Physics

  39. Learning Optimal Dynamic Matching via Graph Neural Networks

    Jul 31, 2026Genta Okada, Shunya Noda, Junpei Komiyama +1Bipartite Perfect MatchingsMatching Markets

  40. A Unified Benchmark of Deep Learning Models for Multi-task 3D Brain Tumor Segmentation from Magnetic Resonance Imaging

    Jul 30, 2026Diego J. Torrejón, Luna Y. Hernández, Javier SánchezBrain Tumor SegmentationMagnetic Resonance Imaging

  41. Feature Interaction Modeling for Neural Operators

    Jul 30, 2026Quan Gu, Xiaoduo Li, Hongxia LiuConventional Physics-Informed Neural NetworksPartial Differential Equations

  42. Simplifying Neural Networks During Training

    Jul 30, 2026Lorenzo Sciandra, Samuele Fonio, Roberto EspositoNeural CollapseDeep Network

  43. Latent States in Neural Networks: Recovering the Temporal Structure of Drifting Data from Model Weights

    Jul 29, 2026Kevin GuanLatent StatesModel Weights

  44. Universality and Approximation Rates of Graph Neural Networks with Random Features

    Jul 29, 2026Lukas Gonon, Thilo Meyer-Brandis, Niklas WeberGraph Neural NetworksNeural-Network Approximation

  45. From Conceptual Hydrologic Models to Conceptually Interpretable Neural Networks: A Snow-Water Mass-Conserving-Perceptron Framework for Discovering Catchment-Scale Precipitation-Storage-Runoff Representations

    Jul 29, 2026Yuan-Heng Wang, Hoshin V. GuptaFundamental Hydrological PrinciplesMultilayer Perceptrons

  46. EvoPINN: Agentic Discovery of Executable Algorithms for Physics-Informed Neural Networks

    Jul 29, 2026Peng Yin, Kai Li, Yifan Zhang +1Conventional Physics-Informed Neural NetworksPartial Differential Equation Benchmarks

  47. Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks

    Jul 29, 2026Shuhei IkemotoBackpropagationNeural Network

  48. Examining the Efficacy of Graph Neural Network Message-Passing in Regression Contexts

    Jul 29, 2026Keith G. Mills, Aedan J. DeFrates, Joong Ho KimGraph Neural NetworksMessage Passing Neural Networks

  49. More Data, Worse Decisions? Preference Reversals in Neural Networks under Gram Incompatibility

    Jul 28, 2026Yanli Yan, Yuanzheng Li, Yong Zhao +2Bias LearningDecisions

  50. Are the High-weight Neurons the Important Ones in Image Classification Neural Networks?

    Jul 28, 2026Qitao Chen, Dongfu Yin, F. Richard YuImportanceNeural Network

  51. Algorithmic Separation between Constant-Depth and Logarithmic-Depth Neural Networks

    Jul 28, 2026Yunwei Ren, Zihao Wang, Jason D. LeeDeep NetworkNeural Network

  52. Fourier Feature Physics-Informed Neural Networks for Elasto-Plastic Analysis of Geomaterials with a Non-Associative Mohr-Coulomb Model

    Jul 27, 2026Apisit Robjanghvad, Sompote YouwaiFinite Element MethodConventional Physics-Informed Neural Networks

  53. Learning to Resolve Neutron Resonances with Fully Convolutional Neural Networks

    Jul 27, 2026Nataly R. Panczyk, Athanasios Stamatopoulos, Josef Svoboda +1Nuclear DataConvolutional Neural Networks

  54. Enabling Fully Integer-Only Inference for Lightweight Detection Transformers

    Jul 27, 2026Thanh Cong Le, Michal Szczepanski, Martyna PorebaSelf-Supervised Vision TransformersRt-Detr

  55. Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms

    Jul 27, 2026Michael Pürrer, Ashwin Girish, Lucy M. Thomas +2Binary Black Hole MergersGravitational Waves

  56. Physics-Informed Neural Networks for Predicting Nitrous Oxide Flux

    Jul 26, 2026Freddy Yu, Jashanjeet Kaur Dhaliwal, Subhadeep ChakrabortyNitrogenCarbon Emissions

  57. A Comparison of Data Augmentation Methods for Training Deep Neural Networks on Synthetic Aperture Sonar

    Jul 26, 2026C. J. Moore, Gregory D. Vetaw, Jordan MalofSynthetic Data AugmentationAugmentation

  58. Physics-Informed Neural Networks for Discovering Periodic Orbits in the Gravitational Three-Body Problem

    Jul 26, 2026Nikolaos Kollias, Nikolaos MatzakosConventional Physics-Informed Neural NetworksNear-Earth Objects

  59. LAWFUL: Law-Aligned Witness for Faithful Use of Latents

    Jul 26, 2026Kevin Chen, Kenneth W. Parker, Anish AroraModel InterpretabilityInductive Logic Programming

  60. A Statistical Difference between Single-Layer Learning and Hierarchical Learning in Wide Neural Networks

    Jul 26, 2026Sumio WatanabeTwo-Layer Neural NetworksNeural Network