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

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. Leveraging Energy Features for Surface Classification with Deep Learning: A Comparative Analysis Across Three Independent Datasets

    Jun 17, 2026Alexander Belyaev, Oleg KushnarevDeep LearningEnergy Resources

  2. Effects of sparsity and superposition on loss in simple autoencoders

    Jun 16, 2026Mriganka Basu Roy Chowdhury, Eric McLaughlin WeinerImproving Sparse AutoencodersActivation Functions

  3. What Does the Weight Norm Control in Grokking? Logit-Scale Mediation under Cross-Entropy

    Jun 16, 2026Truong Xuan KhanhGrokkingBatch Normalization

  4. Measurement noise limits the advantage of nonlinear models over linear models in biomedical prediction

    Jun 16, 2026Marc-Andre Schulz, Kerstin RitterLogistic RegressionClinical Prediction

  5. Looped World Models

    Jun 16, 2026Hongyuan Adam Lu, Z. L. Victor Wei, Qun Zhang +28World ModelsNeural Architectures

  6. Neural Network Implementation of the Renormalization Group for Fault Diagnosis with Class Imbalance

    Jun 16, 2026Evgeny Nikulchev, Dmitry IlinRenormalization GroupClass Imbalance

  7. A Convex Quasilinearization Method for Solving Nonlinear PDEs with Physics-Informed Neural Networks

    Jun 16, 2026Gbenga T. Awojinrin, Abdul-Akeem Olawoyin, Rami M. YounisConventional Physics-Informed Neural NetworksPartial Differential Equations

  8. Why SWAVE May Not Be All You Need:A Concept-Evolution Retrospective on Complex-Valued Recurrent Language Models

    Jun 16, 2026Ramprasath Ganesaraja, Swathika N, Sahil Dilip PanseRecurrent ModelNeural Architectures

  9. Catastrophic Forgetting is Low-Rank: A Function-Space Theory for Continual Adaptation

    Jun 16, 2026Ido Nitzan Hidekel, Dan RavivCatastrophic ForgettingNeural Tangent Kernel

  10. Structural Preservation and the Logical Expressiveness of Graph Neural Networks

    Jun 16, 2026Przemysław Andrzej Wałęga, Bernardo Cuenca GrauGraph Neural NetworksModal Logic

  11. Conservation Laws for Modern Neural Architectures

    Jun 16, 2026Viet-Hoang Tran, Vinh Khanh Bui, Tan Lai Ngoc +3Gradient FlowOver-Parameterized Neural Networks

  12. Geometrical fairness in graph neural networks

    Jun 16, 2026Arturo Pérez-Peralta, Sandra Benítez-Peña, Blas Kolic +1Fairness-Aware LearningGraph Neural Networks

  13. Physics-Constrained Neural Networks for Improved Short-Term Weather Forecasting: A Case Study over the South Pacific

    Jun 16, 2026Egor Bugaev, Fedor Buzaev, Dmitry Efremenko +2Numerical Weather PredictionArtificial Intelligence Weather Models

  14. A Link between Shock-wave Theory and Symmetry-reduced Stochastic Gradient Descent for Artificial Neural Networks

    Jun 16, 2026Taiki MiyagawaTwo-Layer Neural NetworksStochastic Gradient Descent

  15. Sobolev Approximation by Fixed-Size Neural Networks with Arbitrary Accuracy

    Jun 15, 2026Baicheng Li, Haizhao Yang, Shijun ZhangNeural-Network ApproximationLogarithmic Sobolev Inequalities

  16. Multi-Modal Spatio-Temporal Graph Neural Network with Mixture of Experts for Soil Organic Carbon Prediction

    Jun 15, 2026Daniele Mos, Felipe Drummond, Anton Bossenbroek +1Soil Moisture EstimationSoil

  17. On the Entropy Formula for Real, Complex, and Quaternionic Deep Linear Networks

    Jun 15, 2026Luis Contreras, Marco Nahas, Tejas KotwalDeep NetworkQuaternion

  18. RepNN: Tackling spectral bias in deep neural networks via parameter reparameterization

    Jun 15, 2026Yong Wang, Tao Zhou, Xuhui MengReparameterizationRectified Linear Unit

  19. TNODEV: Toolbox for Neural ODE Verification

    Jun 15, 2026Abdelrahman Sayed Sayed, Pierre-Jean Meyer, Mohamed GhazelNeural Network VerificationNeural Ordinary Differential Equations

  20. Robust Neural Tucker Factorization with Bias Correction and Adaptive Initialization

    Jun 15, 2026Yuchao Su, Yixin RanTensor CompletionNonnegative Matrix Factorization

  21. Surpassing Scale by Efficiency: A Compact 135M Parameter Foundational LLM Natively Adapted for the Bangla Language

    Jun 15, 2026Rabindra Nath NandiBanglaSmall Language Models

  22. Learned JPEG Compression for DNN Vision

    Jun 15, 2026Kaixiang Zheng, Ahmed H. Salamah, Siyu Chen +1Learned Image CompressionModern Deep Networks

  23. The Third Challenge on Image Denoising at NTIRE 2026: Methods and Results

    Jun 14, 2026Lei Sun, Hang Guo, Bin Ren +6Image RestorationImage Denoising

  24. The Information-Theoretic Benefit of Shared Representations under Orthogonality Constraints

    Jun 14, 2026Thomas Dittrich, Oliver Potocki, Philipp GrohsNeural-Network ApproximationInformation-Theoretic Limits

  25. An Integrated System for Real-Time Student Assessment and Career Guidance Using Neural Networks in Computing Disciplines

    Jun 14, 2026Sakir Hossain Faruque, Md. Jubair Hossain, Sharun Akter KhushbuComputer ScienceStudent

  26. Z-Plane Neural Networks: Bounded Geometric Activation Replaces ReLU and LayerNorm

    Jun 14, 2026Sungwoo Goo, Hwi-yeol Yun, Sangkeun JungActivation FunctionsBatch Normalization

  27. PHINN: Persistent Homology Inspired Neural Network for Rare-Event Time Series Generation

    Jun 13, 2026Emre Yusuf, Ren Takahashi, Jayabrata BhaduriSynthetic Time SeriesGenerative Models

  28. Rethinking the Role of Efficient Attention in Hybrid Architectures

    Jun 13, 2026Ziqing Qiao, Yinuo Xu, Chaojun Xiao +6Sliding-Window AttentionEfficient Long-Context Inference

  29. Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model

    Jun 13, 2026Siyu Chen, Beining Wu, Miao Lu +2Optimal Sample ComplexityTwo-Layer Neural Networks

  30. AI Engram: In Search of Memory Traces in Artificial Intelligence

    Jun 12, 2026Jea Kwon, Dong-Kyum Kim, Jiwon Kim +3Dense Associative MemoryDeep Network

  31. FlexPooling with Simple Auxiliary Classifiers in Deep Networks

    Jun 12, 2026Muhammad Ali, Omar Alsuwaidi, Salman KhanConvolutional Neural NetworksDeep Network

  32. Test-Time Adaptation of Spiking Neural Networks for Intracortical Neural Decoding using Membrane Potential Alignment

    Jun 12, 2026Guangzhi TangSpiking Neural NetworksBrain-Computer Interface

  33. Compressed Computation is (probably) not Computation in Superposition

    Jun 12, 2026Jai Bhagat, Sara Molas-Medina, Giorgi Giglemiani +1Context CompressionRectified Linear Unit

  34. A Comparative Study of Deep Learning Architectures for Multi-Horizon Behavioural Forecasting for Mobile Health

    Jun 12, 2026Pavlos Nicolaou, Kleanthis Malialis, Artemis Kontou +1Wearable DevicesDeep Learning

  35. Fodor and Pylyshyn's Systematicity Challenge Still Stands

    Jun 12, 2026Michael Goodale, Salvador MascarenhasCognitive ScienceNeural Network

  36. Leptomeningeal Collateral Detection on DSA via Vessel-Graph Neural Networks

    Jun 12, 2026Junyong Cao, Hakim Baazaoui, Chinmay Prabhakar +5Coronary AngiographyStroke

  37. On-Device Neural Architecture Search

    Jun 12, 2026Andrea Mattia Garavagno, Edoardo Ragusa, Paolo Gastaldo +2Neural Architecture SearchNeural Architectures

  38. Can Deep Neural Networks Improve Compression of Very Large Scientific Data?

    Jun 12, 2026Muhannad Alhumaidi, Guozhong Li, Spiros Skiadopoulos +1Context CompressionPredictive Coding

  39. Co-Evolved Spiking Neural Network Ensembles via Marginal Contribution Fitness

    Jun 12, 2026Catherine Rodriquez, James GhawalySpiking Neural NetworksCo-Evolution

  40. Multi-Variable Stellar Parameter Estimation Using Residual Multitask Neural Networks

    Jun 11, 2026Bruno Santos Meneses Barreto, Marcio EisencraftBillion-Parameter ModelsResidual Connections

  41. Neural Variability Enhances Artificial Network Robustness

    Jun 11, 2026Robin Preble, Praveen Venkatesh, Stefan Mihalas +1Neural Network

  42. Clustering Node Attributed Networks with Graph Neural Networks and Self Learning

    Jun 11, 2026Rodrigo de Sapienza Luna, Daniel Ratton FigueiredoGraph Neural NetworksImage Clustering

  43. Connections Between Pairs of Filters Improve the Accuracy of Convolutional Neural Networks

    Jun 11, 2026Kathleen Anderson, Philipp Grüning, Erhardt BarthConvolutional Neural NetworksActivation Functions

  44. Neural Architectures as Functional Priors in Physics-Informed Control Problems

    Jun 11, 2026Sonia Rubio Herranz, Fernando Carlos López Hernández, Antonio López MontesNeural ControlConventional Physics-Informed Neural Networks

  45. On Subquadratic Architectures: From Applications to Principles

    Jun 10, 2026Anamaria-Roberta Hartl, Levente Zólyomi, David Stap +6Sequence ModelingNeural Architectures

  46. Adjoint Method versus Physics-Informed Neural Networks in PDE-Constrained Inverse Problems

    Jun 10, 2026Zhen Zhang, Alessandro Alla, George Em KarniadakisConventional Physics-Informed Neural NetworksIll-Posed Inverse Problem

  47. SpikeDecoder: Realizing the GPT Architecture with Spiking Neural Networks

    Jun 10, 2026Claas Beger, Florian Walter, Alois KnollSpiking Neural NetworksTransformer Encoder

  48. Multi-Rate Mixture of Experts for Accelerating Liquid Neural Network Training

    Jun 10, 2026Shilong Zong, Almuatazbellah Boker, Hoda EldardiryMultivariate Time Series ForecastingSpatial Attention

  49. StanceNakba Shared Task: Actor and Topic-Aware Stance Detection in Public Discourse

    Jun 10, 2026Kholoud K. Aldous, Md Rafiul Biswas, Mabrouka Bessghaier +3Tweet-Level Stance DetectionSentiment Analysis

  50. SpikeTAD: Spiking Neural Networks for End-to-End Temporal Action Detection

    Jun 10, 2026Min Yang, Mi Zhou, Limin WangTemporal Action LocalizationBinary Spikes

  51. Family-Aware Residual Architecture for Predicting Quantum Circuit Simulation Performance

    Jun 10, 2026Honjar Xing, Yehong Jiang, Xianbang Wang +2Quantum Circuit SimulationTensor Networks

  52. Physics-Distilled Neural Network enabled by Large Language Models for Manufacturing Process-Property Predictive Modeling

    Jun 10, 2026Ge Song, Kiarash Naghavi Khanghah, Anandkumar Patel +2Physics-Informed Machine LearningPredictive Maintenance

  53. Energy-Conserved Neural Pipelines: Attenuating Error Propagation in Modular Neural Networks via Physical Conservation Constraints

    Jun 9, 2026David Young, Swan Yi HtetNeural NetworkNormalization

  54. Learning from almost nothing: How neural networks survive heavy input corruption

    Jun 9, 2026Justin Tahmassebpur, Asadullah Bhuiyan, Hyejin Kim +1Noisy LabelsNeural Network

  55. Robust Regression of General ReLUs with Queries

    Jun 9, 2026Ilias Diakonikolas, Daniel M. Kane, Mingchen MaRectified Linear UnitOptimal Sample Complexity

  56. Limitations of Learning Tanh Neural Networks with Finite Precision

    Jun 9, 2026Philipp Grohs, Matěj TrödlerNeural NetworkFull-Precision Performance

  57. Conservation Laws from Data Symmetry in Neural Networks

    Jun 9, 2026Jakob Galley, Vahid Shahverdi, Axel FlinthEquivariant Neural NetworksSymmetry

  58. A Unified Siamese Learning Framework for Zero-Day Anomaly Detection and Classification in Optical Networks

    Jun 9, 2026Carlos Natalino, Flávia P. Monteiro, Paolo MontiZero-Shot Anomaly DetectionOptical Networks

  59. PL-KKT-hPINN: Enforcing Nonlinear Equality Constraints on Neural Networks via Piecewise-Linear Projection

    Jun 9, 2026Fateme Mohammad Mohammadi, Hector Budman, Joshua L. PulsipherConventional Physics-Informed Neural NetworksInequality Constraints

  60. Towards Critical Branching Mechanism in Recurrent Neural Networks

    Jun 9, 2026Feixiang Ren, Ling FengRecurrent Neural NetworksBifurcation