Neural Network

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Neural ArchitecturesActivation FunctionsDeep NetworkTwo-Layer Neural NetworksRectified Linear Unit NetworksNeural Tangent KernelModern Deep NetworksRectified Linear Unit

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Period ending 2026-09-21

15 new papers

A weekly snapshot of new work published in Neural Network.

Period ending 2026-09-14

2 new papers

A weekly snapshot of new work published in Neural Network.

Period ending 2026-09-07

16 new papers

A weekly snapshot of new work published in Neural Network.

658 papers

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  1. Graph Neural Networks for the Graphical Bootstrap

    Jul 3, 2026Rigers Aliaj, Gabriele Dian, Reza Doobary +1Graph Neural NetworksNeural Network

  2. A Spiking Sequence Generator for Polar Trajectories on Neuromorphic Hardware

    Jul 2, 2026William R. P. Nourse, Roger D. QuinnNeuromorphic HardwareNeural Control

  3. CodeJeNN: A simple C++ neural network generator for physics applications

    Jul 2, 2026Jay Arcities, Pavel Popov, Eric J Ching +2C++Cuda

  4. An Optimisation Framework for the Well-Conditioned Training of Physics-Informed Neural Networks

    Jul 2, 2026Joseph Webb, Sadok Jerad, Coralia CartisConventional Physics-Informed Neural NetworksNewton

  5. Predicting Early Stages Of Alzheimer's Disease And Identifying Key Biomarkers Using Deep Artificial Neural Network And Ensemble Of Machine Learning Methodologies

    Jul 2, 2026Debopriya GhoshAlzheimerBiomarker

  6. Schedulable Job-Level Dependencies for Cause-Effect Chains via Graph Neural Networks

    Jul 2, 2026Silviu S. Craciunas, Christian Hakert, Jian-Jia Chen +2Constraint-Aware SynthesisGraph Neural Networks

  7. Born Discrete, Made Smooth: Variational Formulation of Shallow Neural Networks

    Jul 2, 2026Matej Benko, Pierre Bousquet, Iwona Chlebicka +1Two-Layer Neural NetworksVariational

  8. Muon as a Residual Connection

    Jul 1, 2026Hao HuangMuon OptimizerMuon

  9. Predicting Lethal Outcome (Cause) And Understanding Key Biomarkers Linked With Acute Myocardial Infarction Using Deep Artificial Neural Network And Ensemble Of Machine Learning Methodologies

    Jul 1, 2026Sagnik GhoshBiomarkerMachine Learning

  10. K-Inverse-RFM: A Modified RFM that Bridges the Gap to Neural Networks for Data-Corrupted Mathematical Tasks

    Jul 1, 2026Gil PasternakFeature LearningExtreme Class Imbalance

  11. Self-Organized Learning in Oscillatory Neural Networks with Memristive Signed Couplings

    Jul 1, 2026Riley Acker, Aman Desai, Garrett Kenyon +1Neuromorphic HardwareResistive Random Access Memory

  12. Computer vision-based neural networks for radioisotope identification in urban environments

    Jun 30, 2026Masen Bachleda, Peter LalorRadio FrequencyConvolutional Neural Networks

  13. Representation as a Bottleneck for Mechanistic Interpretability: The Manifestation Unit Protocol

    Jun 30, 2026Hussein Chouman, Wataru Sasaki, Tomokazu Matsui +2Mechanistic InterpretabilityModel Interpretability

  14. Low-dimensional topology of deep neural networks

    Jun 30, 2026Junyu Ren, Lek-Heng LimFeed-Forward NetworkNeural Network

  15. Intrinsically Stable Spiking Neural Networks: Overcoming the Performance Barrier in the Absence of Batch Normalization

    Jun 30, 2026Ruichen Ma, Xiaoyang Zhang, Jian Bai +5Spiking Neural NetworksNeuromorphic Hardware

  16. Robustness of neural networks to random noise perturbations of their inputs

    Jun 30, 2026Mark Levene, Martyn HarrisNeural NetworkPerturbations

  17. Domain-Decomposed Randomized Neural Networks for Partial Differential Equations in Unbounded Domains

    Jun 30, 2026Haixin Wang, Haoning Dang, Fei Wang +1Partial Differential EquationsBayesian Quadrature

  18. Explaining Machine Learning and Memorization with Statistical Mechanics

    Jun 30, 2026Robin TheriaultDense Associative MemoryMachine Learning

  19. Fast approximation and learning of binary classification tasks in o-minimal structures using ReLU neural networks

    Jun 29, 2026Clemens Kinn, Philipp PetersenRectified Linear Unit NetworksBinary Classification

  20. Dynamic Prediction of Alternating Recurrent Events via Neural Network

    Jun 29, 2026Abigail Loe, Susan Murry, Zhenke WuRecurrenceTime-To-Event Data

  21. Implementation of Hyperelastic Physics-Augmented Neural Networks in the Explicit Finite Element Codes Simcenter Radioss and OpenRadioss with Applications to Impact Events

    Jun 29, 2026Lukas Maurer, Sascha Eisenträger, Marian Bulla +1Finite Element MethodConventional Physics-Informed Neural Networks

  22. A Coherence Law for Trainability in Noisy Equivariant Quantum Neural Networks

    Jun 28, 2026Hassan Ugail, Newton HowardQuantum Neural NetworksHamiltonian

  23. Unified Complex-valued Neural Network: A Magnitude-Phase Computational Model for Event-Driven Neuromorphic Learning

    Jun 27, 2026Reza Ahmadvand, Sarah Safura Sharif, Yaser Mike BanadNeuromorphic HardwareBinary Spikes

  24. On Surrogate Modeling of Static Response of AM Short-Fiber Thermoplastics Using Graph Neural Networks

    Jun 27, 2026Pharindra Pathak, Vipin Kumar, Trenton M. Ricks +2CompositesPorous Media

  25. Closed-Form Steepest Descent Direction toward Flat Minima: Reducing Upper Bounds on the Loss Hessian Eigenspectrum in Neural Networks

    Jun 27, 2026Yuto Omae, Kazuki Sakai, Yohei Kakimoto +3Condition NumberGradient Descent

  26. Spectral phase transitions and trainability in neural network learning dynamics

    Jun 26, 2026Chanju Park, Dario Bocchi, Francesco D'Amico +2Neural NetworkModel Weights

  27. Bridging Ab Initio Symmetries and Global Nuclear Masses with Interpretable Neural Networks

    Jun 26, 2026Phong Dang, Evander Espinoza, Xiaoliang Wan +6Nuclear DataSymmetry

  28. Parameter-Efficient Continuous-Variable Photonic Quantum Neural Networks for Edge Quantum AI: Demonstration in Oral Cancer Detection

    Jun 26, 2026Akshay Bhagwan Sonawane, Sophie Choe, Lakshman TamilHybrid Quantum Neural NetworksQuantum Machine Learning

  29. How Width and Data Shape Generalization Scaling Laws in Quadratic Neural Networks

    Jun 26, 2026Julius Girardin, Emanuele Troiani, Yizhou Xu +3Two-Layer Neural NetworksScaling Laws

  30. Recovering Sharp Conductivity Features in the Finite-Data Calderón Problem with Physics-Informed Neural Networks

    Jun 26, 2026Ali AlHadi Kalout, Pablo Tejerina-Pérez, Konstantin Karchev +5Conventional Physics-Informed Neural NetworksBoundary Value Problems

  31. Physics-constrained neural networks for surrogate modeling of lossless periodic structures

    Jun 26, 2026Eric Prehn, Peter JungWaveConventional Physics-Informed Neural Networks

  32. Criticality-Constrained Iterative Pruning for Energy-Efficient Spiking Neural Networks via Combined Importance Scoring

    Jun 26, 2026Muhammad HamzaSpiking Neural NetworksNeuromorphic Hardware

  33. WattLayer: Get Layers Right to Estimate Inference Energy of Neural Networks

    Jun 26, 2026Adrien Sardi, Marie-Line Alberi Morel, Sara Alouf +2Artificial Intelligence InfrastructureOnline Inference

  34. SpikeVLA: Vision-Language-Action Models with Spiking Neural Networks

    Jun 26, 2026Ruiqi Song, Dujun Nie, Siyu Teng +7Vision-Language-Action ModelsReal-Time Inference

  35. CANNs: A Toolkit for Research on Continuous Attractor Neural Networks

    Jun 26, 2026Sichao He, Aiersi Tuerhong, Shangjun She +4Human Visual CortexAttractors

  36. Learning 1-Bit LiDAR-based Localization with Auxiliary Objective

    Jun 26, 2026Kaijie Yin, Zhiyuan Zhang, Tian Gao +3Sequential Visual LocalizationLight Detection And Ranging

  37. The Simulacrum: Decision-Theoretic Pretraining for Near-Optimal Time-Series Forecasting and Inference

    Jun 26, 2026Pablo Montero-Manso, Marcel ScharthMultivariate ForecastingFinite-Sample

  38. Graph Neural Networks Applications Across Domains: All Insights You Need

    Jun 25, 2026Abderaouf BahiGraph Neural NetworksNeural Network

  39. Explaining Temporal Graph Neural Networks via Feature-induced Information Flow

    Jun 25, 2026Ping Xiong, Thomas Schnake, Klaus-Robert Müller +1Temporal Graph Neural NetworksNeural Network

  40. fTNN: a tensor neural network for fractional PDEs

    Jun 25, 2026Qingkui Ma, Hehu Xie, Xiaobo YinFourier Neural OperatorsBayesian Quadrature

  41. Symplectic Neural Networks for learning Generalized Hamiltonians

    Jun 25, 2026Harsh Choudhary, Vyacheslav Kungurtsev, Chandan Gupta +2HamiltonianNeural Ordinary Differential Equations

  42. Scalable Message-Passing Quantum Graph Neural Networks in the Weisfeiler-Leman Hierarchy

    Jun 25, 2026Snehal Raj, Brian Coyle, Léo Monbroussou +3Variational Quantum CircuitsNeural Network

  43. Data-driven Machine Learning Cannot Reach Symbolic-level Logical Reasoning -- The Limit of the Scaling Law

    Jun 24, 2026Tiansi Dong, Mateja Jamnik, Pietro LiòNeuro-Symbolic FrameworkNeural Network

  44. Equivariance and Augmentation for Bayesian Neural Networks

    Jun 24, 2026Miaowen Dong, Axel Flinth, Jan E. GerkenBayesian Neural NetworksEquivariant Neural Networks

  45. Topology-Informed Neural Networks for Flood Detection in Optical and Synthetic Aperture Radar Imagery

    Jun 24, 2026Sophia Li, Max Zhao, Raghu G. Raj +1Flood DetectionSen1Floods11

  46. Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors

    Jun 24, 2026Alexander Hägele, Alejandro Hernández-Cano, Atli Kosson +1Neural Network OptimizationModel Weights

  47. An Integrated Hardware-Software Design for Low-Data Spatial Defect Detection in Robotic Visual Inspection with Hybrid Optoelectronic Neural Networks

    Jun 24, 2026Chaoqing Tang, Jiaxuan Li, Huanze Zhuang +4Scalable Defect DetectionRobotic Perception

  48. Pre-Warm: Initializing Convolutional Filters from First-Batch Patch Dictionaries

    Jun 24, 2026Rowan MartnishnConvolutional Neural NetworksConvolutional

  49. Silent Failures in Physics-Informed Neural Networks: Parameter Poisoning and the Limits of Loss-Based Validation

    Jun 23, 2026David McShannon, Nicholas DietrichConventional Physics-Informed Neural NetworksPartial Differential Equation Benchmarks

  50. Manifold Constrained Tabular Deep Neural Networks

    Jun 23, 2026Tian Li, Lucy Robinson, Varun Ojha +1Tabular LearningHyperbolic Learning

  51. Can Scale Save Us From Plasticity Loss in Large Language Models?

    Jun 23, 2026J. Fernando Hernandez-Garcia, Tomás Figliolia, Beren MillidgeLarge ModelsPlasticity

  52. Extended pseudo-spectral physics-informed neural networks for phase-field models

    Jun 23, 2026Callum Marsh, Radek Erban, Andreas MunchConventional Physics-Informed Neural NetworksNeural Fields

  53. Spatial Partial Functionalization of Neural Networks based on Noise Fields

    Jun 23, 2026Shuhei Ikemoto, Fabio DallaLiberaNeural FieldsNeural Network

  54. Identifying structural design principles shaping the computational abilities of recurrent neural networks

    Jun 22, 2026Tom Talpir, Elad SchneidmanRecurrent Neural NetworksNeural Network

  55. Reconstructing GRACE Terrestrial Water Storage with Spatio-Temporal Graph Neural Networks: An Application to South America

    Jun 22, 2026Lukas Arzoumanidis, Lara Johannsen, Klara Middendorf +2Sea-Surface Temperature DataTemporal Graph Neural Networks

  56. Neural Networks as Linear Regression: An Introduction for Statisticians

    Jun 22, 2026Abigail Loe, Susan Murray, Zhenke WuNeural NetworkStatistical Inference

  57. SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations

    Jun 22, 2026Nandana Menon, Giorgio ValloneGnn-Based DetectorsMagnetic Tunnel Junction

  58. Sublinearly Structured Deep Neural Networks Achieve Feature Learning Consistency for Compositional Functions

    Jun 22, 2026Sehwan Kim, Yan Sun, Faming LiangModern Deep NetworksNeural Network

  59. Quantum Convolutional Neural Networks for Groundwater Heat Plume Prediction: A Surrogate Modeling Approach

    Jun 22, 2026Danyal Maheshwari, Julia Pelzer, Miriam SchulteQuantum Neural NetworksSurrogate Models

  60. Convergence of Gradient Descent for General Neural Network Architectures Beyond the NTK Regime

    Jun 22, 2026Yuqing WangNeural Tangent KernelGradient Descent