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8 papers in the last four weeks, up 167% on the four weeks before. 0.1% of all new papers.

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  1. A Response Theory Probe for Learned Stochastic AI Simulators, Tested on Lorenz-63

    Oct 5, 2026João Böger, Simon Driscoll, Niccolò Zagli +2EmulatorsChaos

    Department of Technology, Management and Economics Technical University of Denmark Kongens Lyngby, 2800, DK · Department of Applied Mathematics and Theoretical Physics University of Cambridge Cambridge, CB3 0WA, UK · School of Computing and Mathematical Sciences University of Leicester Leicester, LE1 7RH, UK +1

  2. Neuromorphic Pseudo-Random Number Generators with a Low Power Hardware Implementation

    Sep 30, 2026Jafar Shamsi, Navid Akbari, Sonia Sennik +2Neuromorphic ComputingField-Programmable Gate Arrays

    Hotchkiss Brain Institute, University of Calgary, Calgary, Canada · Biomedical Engineering, University of Calgary, Calgary, Canada · Electrical and Software Engineering, University of Calgary, Calgary, Canada +2

  3. TopTimeNet: Topologically-assisted time-series classification model

    Sep 30, 2026Sharareh Sayyad, Sophia BazziTime-Series ClassificationTopology

    Department of Mathematics and Statistics, Washington State University, Pullman, Washington 99164-3113, USA · European Molecular Biology Laboratory, EMBL Hamburg, c/o DESY, Building 25A, Notkestraße 85, 22603 Hamburg, Germany

  4. Learning Chaos Without Seeing Chaos: Extrapolation of Global Dynamics in Autoregressive Transformers

    Sep 30, 2026Yilun Liu, Yi Zhang, Ganyu Wu +5ChaosAutoregressive Transformers

    Ludwig Maximilian University of Munich · Munich Center for Machine Learning · Technical University of Munich

  5. Massively Parallel Reinforcement Learning with a Chaotic Reconfigurable Clockless Chip

    Sep 28, 2026Eric Oliveira-Gomes, Damien RontaniChip DesignChaos

    CentraleSup´elec and Universit´e de Lorraine, LMOPS UR4423 Laboratory, Metz F-57070, France

  6. Nonequilibrium Phases of Repulsive Self-Attention: Chaos, Attention Condensation, and Emergent Locality

    Sep 23, 2026Qucheng Gao, Zuyi Yang, Xiao ChenAttractorsChaos

    Department of Physics, Boston College, Chestnut Hill, Massachusetts 02467, USA

  7. Data-driven discrete-time deep recurrent neural network-based modeling for dissipative systems

    Sep 23, 2026Tuan Luong, Hyungpil MoonParametric Physics-Informed Neural NetworkRecurrent Neural Networks

    Department of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, South Korea.

  8. Inference of Unknown Dynamical Components Using Next Generation Reservoir Computing: From Chaotic Systems to Climate Data

    Sep 21, 2026Jule Budnick, Andrew Keane, Serhiy YanchukReservoir ComputingDynamical Systems

    School of Mathematical Sciences, University College Cork, Cork, Ireland · Potsdam Institute for Climate Impact Research, Potsdam, Germany

  9. Butterfly Effect and the Kinetic Energy Cascade in Probabilistic Machine Learning Weather Prediction Models

    Sep 16, 2026Jiakai Chen, Joel Oskarsson, Simon Driscoll +1Numerical Weather PredictionArtificial Intelligence Weather Models

    Department of Physics, University of Cambridge, Cambridge, UK · ETH AI Center, ETH Zurich, Zurich, Switzerland · Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK

  10. Data-Driven Discovery of Composition-Dependent Constitutive Models for Hyperelasticity and Viscoelasticity of Digital Materials

    Sep 3, 2026Josué García-Ávila, Beijun Shen, Manuel K. Rausch +2Chaos

    Department of Mechanical Engineering, Columbia University, New York City, USA · Department of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, USA · Department of Biomedical Engineering, University of Texas at Austin, Austin, USA +1

  11. Ladders in Chaos: When, How, (and Perhaps Why) Does Test-Time Scaling Improve LLM Machine Translation

    Aug 28, 2026Di Wu, Sergey Troshin, Christof Monz +2Test-Time ScalingMachine Translation

    University of Amsterdam · Vrije Universiteit Amsterdam

  12. Semantic Lenia: Emergence of Homeostatic Solitons within the Semantic Space of Large Language Models

    Aug 12, 2026Yoshihiko KayamaSyntactic StructureEmergence

    BAIKA Women’s University 2–19–5, Ibaraki, Osaka, Japan

  13. ChaosProbe: A Neurochaotic Lens on Frozen Transformer Input-Embedding Spaces

    Aug 3, 2026Kunal Kumar Pant, Nithin NagarajTransformer ArchitecturesBehavioral Embeddings

    Department of Electronics and Communication Engineering (ECE) Amrita Vishwa Vidyapeetham Kollam, Kerala, India · Complex Systems Programme National Institute of Advanced Studies (NIAS) IISc Campus, Bengaluru Karnataka, India

  14. Structured Neural Chaos: An Adaptive Surrogate Modeling Framework for Functional Uncertainty Quantification and Global Sensitivity Analysis

    Jul 31, 2026Isabel Corona Guevara, Yeping HuSurrogate ModelsUncertainty Quantification

    Department of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, 80204, CO, USA · Computational Engineering Division, Lawrence Livermore National Laboratory, Livermore, 94550, CA, USA

  15. On a joint simultaneous learning of relevant feature subsets and subspaces in regression-like problems

    Jul 30, 2026Illia HorenkoChaosSubspace

    Chair for Mathematics of AI, Faculty of Mathematics, RPTU Kaiserslautern-Landau, Gottlieb-Daimler-Str. 48, Kaiserslautern, 67663, Germany.

  16. Chaos Is a LADDER: Domain Generalization Beyond Invariance via Reweighting

    Jul 29, 2026Yuhang Jiang, Fengchuan Zhang, Sanguo Zhang +1Multimodal Domain GeneralizationReweighting

    School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China · Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing, China

  17. Natural Invariant Measures for Chaotic Game Dynamics: Finding Order in Chaos

    Jul 23, 2026Jakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski +2ChaosProbability Measures

    Department of Mathematics, Krakow University of Economics, Rakowicka 27, 31-510 Kraków, Poland · Chula Intelligent and Complex Systems Lab, Department of Physics, Faculty of Science, Chulalongkorn University,Bangkok 10330, Thailand · Department of Mathematical Sciences, Indiana University Indianapolis,402 N. Blackford Street, Indianapolis, Indiana 46202, USA +1

  18. Graph-Theoretic Neural Network Fragmentation with Covariant Direct Molecular Force Learning: Enabling Coupled-Cluster Accuracy AIMD for Fluxional Systems

    Jul 23, 2026Xiao Zhu, Srinivasan S. IyengarMolecular DynamicsQuantum Chemistry

    Department of Chemistry, Department of Physics, and the Indiana University Quantum Science and Engineering Center (IU-QSEC), Indiana University, 800 E. Kirkwood Ave, Bloomington, IN-47405

  19. Nipping the Butterfly Effect in the Bud: Self-Output Fine-Tuning for Autoregressive Weather Prediction

    Jul 23, 2026Yun-Ye Cai, Hsuan-Tien LinArtificial Intelligence Weather ModelsShort-Horizon Forecasting

    National Taiwan University · Taipei, Taiwan

  20. Selection Shapes the Boundary: A Preregistered Replication of Monotonicity and Label Agreement in Unselected NLI Populations

    Jul 21, 2026Haram ChoiNatural Language InferenceMonotonicity

    University of Bremen

  21. Image Editing Models are Numerical Solvers

    Jul 21, 2026Ulysse MizrahiMulti-Reference Image GenerationClassical Numerical Solver

    Tel Aviv University

  22. CS-ETS: Chaos-Inspired Samba-Based EMG-To-Speech Synthesis with Nonlinear Chaotic Losses

    Jul 21, 2026Sajid Fardin Dipto, Tarikul Islam Tamiti, David Vergano +2Speech SynthesisChaos

  23. fSRD: Fuzzy Spectral Region Decomposition -- Automated Multi Operator Koopman Representations via an Adaptive Spectral Learning Architecture

    Jul 20, 2026Charles Bokor, Mark Cary, Denise Morrey +1Koopman OperatorSpectral Representation Method

    School of Engineering, Computing and Mathematics Oxford Brookes University Oxford OX33 1HX, UK · Department of Aeronautical and Automotive Engineering Loughborough University Loughborough LE11 3TU, UK

  24. Beyond the Edge of Chaos: Stability-Expressivity Transfer in Reservoir Forecasting

    Jul 20, 2026Yao Du, Xingang WangReservoir ComputingChaos

    School of Physics and Information Technology, Shaanxi Normal University, Xi’an 710062, China

  25. Demodulation of chaotic signals using convolutional neural network

    Jul 18, 2026Mykola Kozlenko, Emrullah Demiral, Anton YudhanaConvolutional Neural NetworksChaos

    SoftServe Inc · Department of Software Engineering, Karabuk University, Türkiye · Department of Electrical Engineering, Universitas Ahmad Dahlan, Yogyakarta, Indonesia

  26. How Much Human Label Variation Does Formal Semantic Structure Explain?: Group-Level Effects and Item-Level Ceilings in NLI

    Jul 17, 2026Haram ChoiNatural Language InferenceInterpretation

    University of Bremen

  27. NeuralChaos: Optimal Adapted Approximation of Square Integrable Predictable Processes

    Jul 15, 2026Anastasis Kratsios, Giulia Livieri, Philipp SchmockerNeural ApproximationsStochastic Differential Equations

  28. Quantum Port-Hamiltonian Neural Networks: Learning Conservative and Dissipative Dynamics via Measurement-Induced Nonlinearity

    Jul 14, 2026Dibakar SigdelQuantum Neural NetworksHamiltonian

    1Mindverse Computing LLC, Lynnwood, WA 98087

  29. A Quantum Reservoir Architecture for Chaotic Forecasting and a Test of Whether Its High Dimension Helps

    Jul 8, 2026Tushar PandeyReservoir ComputingQuantum Learning

    Texas A&M University, College Station, TX, USA

  30. The Multiscale Single-Index Model: A Stylized Model for Hierarchical Feature Learning

    Jul 3, 2026Joan BrunaFeature LearningChaos

    Courant Institute School of Mathematics, Computing and Data Science, New York University

  31. CSympNet-ID: conformal-symplectic map learning for linearly damped Hamiltonian systems

    Jul 3, 2026Jiale Gong, Pengzhan Jin, Dongyang Kuang +2HamiltonianChaos

    School of Mathematics · School of Mathematics (Zhuhai), Sun Yat-sen University, Zhuhai 519082, China · National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing, China +3

  32. Learning dynamical systems from noisy data with Weak-form Kernel Ridge Regression

    Jun 30, 2026Max Kreider, John Harlim, Daning HuangKernel Ridge RegressionDynamical Systems

    Department of Mathematics The Pennsylvania State University, University Park, PA 16802, USA · Department of Mathematics, Institute for Computational and Data Sciences The Pennsylvania State University, University Park, PA 16802, USA · Department of Aerospace Engineering The Pennsylvania State University, University Park, PA 16802, USA

  33. Solving Inverse Problems of Chaotic Systems with Bidirectional Conditional Flow Matching

    Jun 23, 2026Peiyan Hu, Jian Zhang, Jiashu Pan +6Bayesian Inverse ProblemsInverse Problem

    Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China. · Department of Artificial Intelligence, School of Engineering, Westlake University, Hangzhou, Zhejiang, 310030, China. · School of Astronomy and Space Sciences, Chinese Academy of Sciences, Beijing, 100049, China. +4

  34. The Fractal Neural Operator: Overcoming Spectral Bias in Chaotic Attractors via Prime-Harmonic Weierstrass Encodings

    Jun 22, 2026Kanishk AwadhiyaFourier Neural OperatorsChaos

    Independent Researcher

  35. Evolutionary Optimization Reveals Structural Constraints on Reservoir Architecture for Spatiotemporal Chaos

    Jun 22, 2026Nima DehghaniReservoir ComputingChaos

    Department of Physics, MIT · McGovern Institute for Brain Research, MIT

  36. LSTM Variants for Chaotic Dynamical Systems: An Empirical Study on the Lorenz Attractor

    Jun 21, 2026Ruslan GokhmanCnn-LstmChaos

    Yeshiva University

  37. Soliton-like Waves in a Two-Dimensional Recurrent Spiking Neural Network with Weighted Spike-Timing-Dependent Plasticity

    Jun 19, 2026Ch. MeessenSynaptic PlasticitySpiking Neural Networks

    Independent researcher, computational neuroscience, France

  38. Quantum Statistical Memory Advantage Reveals Predictive Structure in Chaotic Invariant Measures

    Jun 11, 2026Maida Wang, Xiao Xue, Minh Chung +1Quantum Computational AdvantageQuantum Machine Learning

    Centre for Computational Science, University College London, London, UK · Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities, Boltzmannstrasse 1, 85748 Garching, Germany · Centre for Advanced Research Computing, University College London, London, UK

  39. First-Order Trajectory Matching: Fast Ensemble Predictions of Chaotic, Turbulent, Stochastic Systems

    Jun 9, 2026Shreya Jha, Timo Schorlepp, Nicholas Geissler +2Stochastic DynamicsSingle Trajectory

    Courant Institute of Mathematical Sciences, New York University

  40. Divide-and-Conquer Modeling for the CTF-4-Science Lorenz Benchmark

    Jun 8, 2026Shundong LiChaosDenoising Trajectory

    Worcester Polytechnic Institute Worcester, MA, USA

  41. Between Amnesia and Chaos: A Memory Stability Expressivity Trilemma for Trainable Dissipative Oscillator Networks

    Jun 7, 2026Caleb MunigetyOscillatory DynamicsReservoir Computing

    Independent Researcher

  42. GENERIC-FNO: Embedding Energy Conservation and Entropy Production into Fourier Neural Operators

    Jun 6, 2026Jason Sulskis, Sathya RaviFourier Neural OperatorsNeural Operators

    Department of Computer Science University of Illinois at Chicago · Electronic Systems Laboratory, Applied Embedded Systems Division Georgia Tech Research Institute

  43. Unified Geometry-Guided ML-FTLE for Tracking Transient Chaos from Scalar Time Series

    Jun 5, 2026S. V. Manivelan, Andrei Velichko, I. ManimehanChaosChange-Point Detection

    Department of Physics, M. R. Government Arts College (Affiliated to Bharathidasan University, Tiruchirappalli), Mannargudi, 614 001, Tamilnadu, India. · Institute of Physics and Technology, Petrozavodsk State University, Petrozavodsk, 185910, Russia.

  44. Empirical Transfer Operators and Finite-Sample Change Detection for Noisy Expanding Interval Maps

    Jun 5, 2026Aparna RajputChange-Point DetectionTransitions

  45. Metric-Aware Hybrid Forecasting for the CTF4Science Lorenz Challenge

    Jun 2, 2026Cen LuShort-Horizon ForecastingChaos

    EPFL & Idiap Research Institute · Switzerland

  46. Order within Chaos: Capturing Intrinsic Energy Anomalies for AI-Manipulated Image Forgery Localization

    Jun 1, 2026Yiming Wang, Baiqi Wu, Qingming Li +3Face Forgery DetectionGenerative Artificial Intelligence

    Zhejiang University, Hangzhou, China.

  47. Learning Chaotic Dynamics through Second-Order Geometric Supervision

    Jun 1, 2026Shinhoo Kang, Hai V. Nguyen, Tan Bui-ThanhChaosJacobian

    Department of Computer Science and Software Engineering, Korea University, Sejong 30019, KR · Department of Aerospace Engineering and Engineering Mechanics, The Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, 2026 TX, USA

  48. On Distributional Reinforcement Learning in Chaotic Dynamical Systems

    May 28, 2026James Rudd-Jones, Mirco Musolesi, María Pérez-OrtizDistributional Reinforcement LearningChaos

    Centre for Artificial Intelligence Department of Computer Science University College London London, UK · Department of Computer Science and Engineering, University of Bologna Bologna, Italy

  49. Adaptive Reservoir Computing for Multi-Scenario Chaotic System Forecasting

    May 27, 2026Shadmehr Zaregarizi, Khashayar YavariReservoir ComputingChaos

    Politecnico di Torino Turin, Italy

  50. Model discovery for dynamical systems with complex-valued product units

    May 26, 2026Martin Brückmann, Babette Dellen, Uwe JaekelDynamical SystemsChaos

    Department of Mathematics, Informatics, and Technology, RheinAhrCampus Remagen University of Applied Sciences Koblenz Joseph-Rovan-Allee 2, 53424 Remagen, Germany

  51. Chaos-SSL: An Attention-Based Self-Supervised Learning Framework with Chaotic Transformation for Medical Image Classification

    May 26, 2026Joao Batista FlorindoMedical Image ClassificationSelf-Supervised Learning

    Institute of Mathematics, Statistics and Scientific Computing, University of Campinas, Rua Sergio Buarque de Holanda, 651, Campinas, Brazil

  52. PIDM-DP: Physics-Informed Diffusion with Dormand-Prince Integration for Chaotic System Identification and State Reconstruction across Multiple Dynamical Regimes

    May 26, 2026Shailendra DabralChaosTime Discretization

    Indian Institute of Technology Indore

  53. A comparative study of accuracy and rollout stability of temporal surrogate models

    May 24, 2026Rajarshi BiswasSurrogate ModelsLong-Horizon Forecasting

    Cargill Inc. Wayzata, MN 55391, USA

  54. ChaosBench-Logic v2: Evaluating LLM Logical Reasoning over Dynamical Systems at Scale

    May 23, 2026Noel ThomasReasoning BenchmarkLLM Reasoning Strategies

    Mohamed bin Zayed University of Artificial Intelligence · Abu Dhabi, UAE

  55. Decomposing Ensemble Spread in Lorenz '96 With Learned Stochastic Parameterizations

    May 21, 2026Birgit Kühbacher, Daan Crommelin, Niki KilbertusGlobal Climate ModelsChaos

    Technical University of Munich, Munich, Germany · Helmholtz Munich, Munich, Germany · Munich Center for Machine Learning (MCML), Munich, Germany +2

  56. Uniform-in-Time Weak Propagation-of-Chaos in Shallow Neural Networks

    May 21, 2026Margalit Glasgow, Joan BrunaTwo-Layer Neural NetworksWasserstein Gradient Flows

    Massachusetts Institute of Technology · Courant Institute School of Mathematics, Computing and Data Science, New York University

  57. Large-Step Training Dynamics of a Two-Factor Linear Transformer Model

    May 20, 2026Krishnakumar BalasubramanianTransformer ArchitecturesGradient Descent

    Department of Statistics, University of California, Davis

  58. Training-Free Bayesian Filtering with Generative Emulators

    May 19, 2026Thomas Savary, François Rozet, Gilles LouppeBayesian FilteringParticle Filters

    SAIL, Montefiore institute, University of Liège, Belgium.

  59. Generative Adversarial Learning from Deterministic Processes

    May 18, 2026Joris C. Kühl, Hanno GottschalkGenerative Adversarial NetworkChaos

    Institute of Mathematics, Technical University of Berlin, Germany

  60. PH-Dreamer: A Physics-Driven World Model via Port-Hamiltonian Generative Dynamics

    May 18, 2026Xueyu Luan, Chenwei ShiWorld ModelsHamiltonian

    School of Electronic and Information Engineering Tongji University Shanghai 200092, China · Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai 200092, China