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9 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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  1. Data, Numbers, and Geometry: Three Tutorials on Numerical Methods, Machine Learning, and Evaluation

    Oct 5, 2026Jessica N. Howard, Yidi Qi, Tomás S. R. SilvaScientific ML

    Instituto de Matemática, Estatística e Computação Científica (IMECC), Universidade Estadual de Campinas (UNICAMP), Rua Sérgio Buarque de Holanda, 651, 13083-859 Campinas, São Paulo, Brazil

  2. An overview of machine learning-enhanced iterative methods for systems of linear and nonlinear equations

    Oct 5, 2026Yuhuang Meng, Jing Zhao, Alexander HeinleinLearning to OptimizeScientific ML

    Delft Institute of Applied Mathematics, Delft University of Technology, Mekelweg 4, Delft, 2628 CD, the Netherlands · Department of Hydrodynamics and Forecasting, Deltares, Boussinesqweg 1, Delft, 2629 HV, the Netherlands

  3. Atoms to Processes: The Role of Artificial Intelligence and Machine Learning in Chemical Engineering

    Oct 1, 2026Michael Baldea, Linda J. Broadbelt, Marianthi G. Ierapetritou +17Scientific MLPhysics-Informed ML

    McKetta Department of Chemical Engineering and Oden Institute for Chemical Engineering and Sciences, The University of Texas at Austin, Austin, TX 78731, USA · Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA · Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716, USA +13

  4. A library for differentiable signal processing and machine learning on the sphere

    Sep 30, 2026Thorsten Kurth, Max Rietmann, Mauro Bisson +6Geometric Representation LearningSpherical Harmonics

    NVIDIA Corporation · California Institute of Technology

  5. A strategic roadmap for an atomistic machine-learning ecosystem

    Sep 30, 2026Jörg Behler, Michele Ceriotti, Cecilia Clementi +46Machine Learning Interatomic PotentialsScientific ML

  6. ALICE: In-context, Zero-shot, Mutual Information Estimation

    Sep 28, 2026Giulio Franzese, Simone Rossi, Pietro MichiardiZero-Shot LearningIn-Context Learning

    EURECOM, Sophia Antipolis, France

  7. The limits of exactness: On the failure of automatic differentiation in physics-informed machine learning

    Sep 27, 2026Ameya D. JagtapAutomatic DifferentiationPDE Surrogate Modeling

    Aerospace Engineering Department, Worcester Polytechnic Institute, Worcester, MA 01609, USA

  8. The Mechanics of Delta Learning: Target Design for Generalizable Scientific Machine Learning

    Sep 23, 2026Kareem M. Gameel, Ihor Neporozhnii, Sjoerd Hoogland +1Residual LearningScientific ML

    Department of Physical and Environmental Sciences, University of Toronto Scarborough Alliance for AI-Accelerated Materials Discovery (A3MD) Toronto, Ontario, Canada · Alliance for AI-Accelerated Materials Discovery (A3MD) Toronto, Ontario, Canada · Department of Chemistry, University of Toronto Department of Physical and Environmental Sciences, University of Toronto Scarborough Alliance for AI-Accelerated Materials Discovery (A3MD) Toronto, Ontario, Canada

  9. Targeted Review for AI-Assisted Biodiversity Surveys: Active Continuous-Score Occupancy Modeling

    Sep 22, 2026Timm Haucke, Lauren Harrell, Justin Kay +2Active LearningHuman-in-the-Loop AI

    MIT · Google Research · The Institute for Bird Populations

  10. Hybrid Physics-AI Framework of Body Center of Mass Dynamics from Wrist-Worn Sensors

    Sep 14, 2026Shuhao Que, Valentina Breschi, Ying WangGait AnalysisWearable Sensing

    Electrical Engineering, University of Twente, Drienerlolaan 5, Enschede, 7522 NB, Netherlands. · Electrical Engineering, Eindhoven University of Technology, Groene Loper 19, Eindhoven, 5612 AP, Netherlands.

  11. SeisBench DAS: A machine learning framework for Distributed Acoustic Sensing

    Sep 7, 2026Jannes Münchmeyer, Han Xiao, Frederik TilmannDistributed Acoustic SensingScientific ML

    GFZ Helmholtz Centre for Geosciences · Institute for Geological Sciences, Freie Universität Berlin, Berlin, Germany

  12. Neural Symbollic Regression Using Deep Learning and Sparse Modelling

    Sep 1, 2026Ravi Kumar U, Sumitra SScientific MLNeurosymbolic Learning

    Department of Mathematics Indian Institute of Space Science and Technology Thiruvananthapuram, India

  13. Knowledge-guided Pattern Discovery via Coupled Tensor Factorizations

    Aug 13, 2026Gaute Johannessen, Geert Roelof van der Ploeg, Evrim AcarTensor DecompositionScientific ML

    Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo · Department of Data Science and Knowledge Discovery, Simula Metropolitan Center for Digital Engineering, Oslo

  14. SEAM: Global consistency beyond local accuracy in scientific machine learning

    Aug 6, 2026Gnankan Landry Regis N'guessan, Bum Jun KimMulti-View ConsistencyExplainable Artificial Intelligence

    Axiom Research Group · Department of Applied Mathematics and Computational Science, The Nelson Mandela African Institution of Science and Technology, 404 Nganana, Kikwe, Arumeru, P.O. Box 447, Arusha, 23311, Tanzania · African Institute for Mathematical Sciences, Research and Innovation Centre, KN 3 Road, Gasharu Cell, Kicukiro Sector, Kicukiro District, Kigali, Rwanda +1

  15. When Proxy Prediction Becomes Equation Reconstruction: Diagnostics and Residual Learning for Factor-Derived Proxy Supervision

    Aug 5, 2026Chayan Lahiri, Ahmed Shafee, Cody FehringerDistribution Shift RobustnessResidual Learning

    Department of Geosciences, Adams State University, Alamosa, Colorado, USA · Department of Computer Science, Adams State University, Alamosa, Colorado, USA · Devils Staircase Wildland Fire Module, Siuslaw National Forest, US Forest Service

  16. Physics-informed reduced-order modelling with equivariant spectral submanifolds

    Aug 4, 2026Georg MaierhoferReduced-Order ModelingScientific ML

    Department of Applied Mathematics and Theoretical Physics · University of Cambridge, UK

  17. TIDE: A Physically Diverse 3D Turbulence Benchmark Dataset for Advancing Scientific Machine Learning

    Aug 4, 2026Yilong Dai, Yiming Sun, Yiheng Chen +4Forecasting BenchmarksScientific ML

    University of Alabama Tuscaloosa, USA · University of Pittsburgh Pittsburgh, USA

  18. MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models

    Jul 31, 2026Boxiao Wang, Runxiang Wang, Kai Li +4Gravitational-Wave AstronomyScientific ML

    National Key Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Advanced Interdisciplinary Sciences, University of the Chinese Academy of Sciences, Beijing, China · School of Astronomy and Space Science, University of the Chinese Academy of Sciences, Beijing, China +2

  19. DFSC: Error-Controlled Differentiable Mittag-Leffler Propagation for Fractional Scientific Machine Learning

    Jul 31, 2026Ning Hu, Haitao Duan, Shuqun Li +1Differentiable ProgrammingScientific ML

    School of Mechanical Engineering, Hangzhou Dianzi University 1158 No. 2 Street, Qiantang District, Hangzhou 310018, China · School of Computer Science, Hangzhou Dianzi University 1158 No. 2 Street, Qiantang District, Hangzhou 310018, China · School of Mathematics and Physics, Xi’an Jiaotong-Liverpool University 111 Ren’ai Road, Suzhou 215123, China +1

  20. Physics-Aligned Self-Supervised Learning for Scientific Imaging

    Jul 30, 2026Bashir Kazimi, Stefan SandfeldData AugmentationScientific ML

    Institute for Materials Data Science and Informatics (IAS-9), Forschungszentrum Jülich GmbH, 52425, Jülich, Germany · Chair of Materials Data Science and Materials Informatics, Faculty 5 – Georesources and Materials Engineering, RWTH Aachen University, 52056, Aachen, Germany

  21. Learning to Trace Seiberg Dualities

    Jul 30, 2026Jonathan J. Heckman, Shani Meynet, Alessandro Mininno +1TransformerScientific ML

    Department of Physics and Astronomy, University of Pennsylvania, 209 South 33rd Street, Philadelphia, PA 19104, USA · Department of Physics, University of Wisconsin–Madison, 1150 University Avenue, Madison, WI 53706, USA

  22. Graph Neural Network Force Fields for Spin Dynamics in Metallic Magnets

    Jul 30, 2026Ali Rayat, Yunhao Fan, Gia-Wei ChernGraph Neural NetworksScientific ML

    Department of Physics, University of Virginia, Charlottesville, VA 22904, USA

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

    Jul 30, 2026Illia HorenkoScientific MLFeature Selection

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

  24. A Lightweight Foundation Model for Collider Physics with Multi-Domain Adaptation

    Jul 29, 2026Liangyu Wu, Qibin Liu, Alexander Yue +1Self-Supervised Pre-TrainingHigh-Energy Physics

    Department of Physics, Stanford University, 450 Jane Stanford Way, Stanford, 94305, CA, USA. · SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, 94025, CA, USA.

  25. From Classification to Regression: Using a Fruitfly to Solve Equations

    Jul 29, 2026Shady E. Ahmed, Panos StinisPrototype-Based LearningSurrogate Modeling

    Advanced Computing, Mathematics, and Data Division Pacific Northwest National Laboratory Richland, WA 99354

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

    Jul 26, 2026Kevin Chen, Kenneth W. Parker, Anish AroraTransformer InterpretabilityMechanistic Interpretability

    Computer Science & Engineering, The Ohio State University, Columbus, Ohio, USA · Independent Researcher, Waterford, Virginia, USA

  27. DeepPySR -- A Symbolic Regression Framework with Dynamic Pruning, Pareto Selection, and Hierarchical Composition for Real-World Scientific Discovery

    Jul 9, 2026Fuling Chen, Kevin Vinsen, Phillip Melton +1Interpretable MLScientific ML

    International Centre for Radio Astronomy Research (ICRAR), University of Western Australia, Perth, WA, Australia · The Raine Study, University of Western Australia, Perth, WA, Australia · Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia +1

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

    Jun 30, 2026Max Kreider, John Harlim, Daning HuangKernel Ridge RegressionKernel Regression

    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

  29. Atompack: A Storage and Distribution Layer for Read-Heavy Atomistic ML Training Datasets

    Jun 29, 2026Ali Ramlaoui, Daniel T. Speckhard, Sagar Pal +3Scientific ML

    Entalpic, Paris, France · Universit´e Paris-Saclay, CentraleSup´elec, Inria, Gif-sur-Yvette, France

  30. Reliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific Models

    Jun 28, 2026Nick Oh, Helen JinInterpretable MLScientific ML

    socius labs, London, United Kingdom · Department of Computer and Information Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States.

  31. Interpreting "Interpretability" and Explaining "Explainability" in Machine Learning in Physics

    Jun 24, 2026Rikab Gambhir, Luisa Lucie-Smith, Jesse ThalerExplainable Artificial IntelligenceInterpretable ML

    Department of Physics, University of Cincinnati, Cincinnati, Ohio 45221, USA · Hamburger Sternwarte, Universität Hamburg, Gojenbergsweg 112, 21029 Hamburg,2026 Germany · Center for Theoretical Physics – a Leinweber Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USAJun +3

  32. Machine Learning and Deep Learning for Exoplanet Detection and Atmospheric Characterization with JWST and the Upcoming Ariel Mission

    Jun 22, 2026Muallim Yakubu, Vwavware Oruaode JudeScientific ML

    Department of Industrial Physics, Enugu State University of Science and Technology · Department of Physics, Dennis Osadebay University, Asaba, Delta State, Nigeria

  33. SPADE: Structure-Prior Adaptive Decision Estimation

    Jun 22, 2026Yifan WangModel SelectionScientific ML

    Department of Mechanical Engineering, McGill University · QC, H3A 2T7, Canada

  34. ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems

    Jun 18, 2026Veronica Saz Ulibarrena, Simon Portegies ZwartReinforcement LearningScientific ML

    Leiden Observatory, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands

  35. Statistical Properties of Training & Generalization

    Jun 18, 2026Itay Lavie, Noam Levi, Yonatan KahnNeural Network GeneralizationScientific ML

    John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA · Tel Aviv University, Tel Aviv, Israel · Department of Physics, University of Toronto and Vector Institute, Toronto, ON, Canada

  36. Investigating Inductive Biases for Machine Learning Emulation of Sudden Stratospheric Warmings in Idealised Isca Simulations

    Jun 17, 2026Oskar Bohn Lassen, Simon Driscoll, Stephen I. Thomson +2Neural Surrogate ModelingClimate Science

    Department of Technology, Management, and Economics Technical University of Denmark · Department of Applied Mathematics and Theoretical Physics University of Cambridge · Department of Mathematics and Statistics University of Exeter

  37. Modeling Doppler Shifts in Radial-Velocity Data with Deep Learning toward Earth-mass Exoplanet Detection

    Jun 16, 2026Isidro Gómez-Vargas, Xavier Dumusque, Yinan Zhao +2Scientific ML

    Department of Astronomy, University of Geneva 51 chemin de Pegasi, 1290 Versoix, Switzerland. · Instituto de Astrofıísica de Andalucía (CSIC), Glorieta de la Astronomía s/n, E-18008 Granada, Spain. · Institute of Space Sciences (CSIC), Carrer de Can Magrans s/n, E-08193 Barcelona, Spain. +3

  38. Domain-Validity-Gated Metamorphic Testing of Scientific ML Surrogates

    Jun 16, 2026Meng Li, Xiaohua Yang, Jie Liu +1Metamorphic TestingScientific ML

    School of Computing, University of South China, Hengyang, China · Hunan Engineering Research Center of Software Evaluation and Testing for Intellectual Equipment, Hengyang, China · CNNC Key Laboratory on High Trusted Computing, Hengyang, China

  39. SciML in the Wild: A Diagnostic Study of When Structural Priors Help and When They Hurt

    Jun 15, 2026Vrishank Sai Anand, Prathamesh Dinesh Joshi, Raj Abhijit Dandekar +2Time Series ForecastingScientific ML

    GEMS Modern Academy Dubai, United Arab Emirates · Vizuara AI Labs, Pune, India

  40. Integrating gene regulatory priors into Transformer attention with scTransformer for interpretable scRNA-seq analysis

    Jun 8, 2026Mikele Milia, Louis Fabrice Tshimanga, Henning Mueller +2Transformer InterpretabilityTransformer Attention

    Department of Information Engineering, University of Padova, Padova, Italy · Department of Neuroscience, University of Padova, Padova, Italy · Padova Neuroscience Center, Padova, Italy +3

  41. From inverse problems to neural operators: prediction, mechanism, and generalization of data-driven models

    Jun 8, 2026Conor RowanScientific DiscoveryScientific ML

    Aerospace Engineering2026 University of Colorado Boulder 3775 Discovery DriveJun 9 Boulder, CO 80309

  42. Instrumented data for causal scientific machine learning

    Jun 5, 2026Daniel N. WilkeScientific ML

    School of Mechanical, Industrial and Aeronautical Engineering, University of the Witwatersrand, Johannesburg, South Africa

  43. Implicit Data Synthesis for Contrastive Unsupervised Data Augmentation

    Jun 5, 2026Patrick Kage, Trevor Hedges, N. Siddharth +1Contrastive LearningSynthetic Data Augmentation

    School of Informatics The University of Edinburgh Edinburgh, Scotland EH8 9AB UK · Massachusetts Institute of Technology Lincoln Laboratory Lexington, MA 02421 USA

  44. Synthics: Synthetic Physics-like Datasets for Machine Learning

    Jun 4, 2026Jari VepsäläinenSynthetic Data GenerationScientific ML

    Mechatronics Department of Energy and Mechanical Engineering School of Engineering Aalto University Finland

  45. Reconstructing Unobservable Temperature Fields via Simulation-Aided Intelligent Sensing

    Jun 3, 2026Monika Stipsitz, Hèlios Sanchis-Alepuz, Jacob Reynvaan +1Synthetic Data GenerationScientific ML

    Embedded Systems Silicon Austria Labs GmbH Graz, Austria

  46. DiffUNet^2: Bidirectional Conditional Diffusion for Probabilistic Scientific Spatiotemporal Modeling

    Jun 2, 2026Mengdi Chu, Jiaxin Yang, Angus G. Forbes +4Diffusion Model GuidanceProbabilistic Forecasting

    Mengdi Chu, Jiaxin Yang, and Han-Wei Shen are with the Ohio State University. · Angus G. Forbes is with NVIDIA. · Nathan Debardeleben, Earl Lawrence, Ayan Biswas are with Los Alamos National Laboratory.

  47. A Geometric Lens on Physics-Aligned Data Compression

    Jun 2, 2026Aleix Segui, Wesley ArmourRate-Distortion TheoryRate-Distortion Optimization

    Department of Engineering Science, University of Oxford, Oxford, UK.

  48. RobustModelMaker: Coupling Bootstrap Stability Selection with Leakage-Safe Nested Cross-Validation for Scientific Machine Learning

    Jun 1, 2026Amanda S BarnardData LeakageScientific ML

    School of Computing Australian National University Acton, ACT 2601

  49. Cellular Sheaf Neural Operators for Structure-Preserving Surrogate Modeling of Constrained PDEs

    May 31, 2026Lennon J. Shikhman, Shane GilbertiePDE Surrogate ModelingScientific ML

    College of Computing, Georgia Institute of Technology, Atlanta, 30332, GA, USA · Department of Aerospace, Physics and Space Sciences, Florida Institute of Technology, Melbourne, 32901, FL, USA

  50. Position: Prioritize Identifying Structure, Not Complex Models, for Scientific Discovery

    May 30, 2026Tyler H. McCormickCausal IdentifiabilityScientific ML

    Departments of Statistics and Sociology, University of Washington, Seattle, WA, USA.

  51. Data-Driven Spectral Prediction for Accelerating Large-Scale Electronic Structure Calculations

    May 29, 2026Abhiram Badrinarayanan, Davor Davidovic, Edoardo Di Napoli +4Quantum ChemistryScientific ML

    Jülich Supercomputing Centre, Forschungszentrum Jülich, Germany · CEA / IRIG / MEM / L_Sim, France

  52. Scientific Machine Learning for Engine Health Management and Remaining Useful Life Prediction

    May 28, 2026Jostein Barry-Straume, Changmin Son, Adrian Sandu +4RUL EstimationPredictive Maintenance

    Computational Science Laboratory Department of Computer Science Virginia Tech Blacksburg, VA 24060

  53. Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization

    May 27, 2026Yuxin Wang, Yuanzhe Hu, Xiaokun Zhong +7Neural Network OptimizationScientific ML

    Dartmouth College · University of California, San Diego · University of California, Berkeley +3

  54. The Perception-Physics Paradox: Probing Scientific Alignment with TC-Bench

    May 23, 2026Dingling Yao, Andrea Polesello, Adeel Pervez +2Representation LearningVision Foundation Models

    Institute of Science and Technology Austria

  55. The Neural Compiler: Program-to-Network Translation for Hybrid Scientific Machine Learning

    May 21, 2026Lucas ShenemanDifferentiable ProgrammingScientific ML

    Institute for Interdisciplinary Data Sciences University of Idaho

  56. Hyrax: An Extensible Framework for Rapid ML Experimentation and Unsupervised Discovery in the Era of Rubin, Roman, and Euclid

    May 18, 2026Aritra Ghosh, Drew Oldag, Michael Tauraso +29Scientific ML

    Dept. of Astronomy & the DiRAC Institute, University of Washington, Box 351580, Seattle, WA 98195, USA · eScience Institute, University of Washington, Seattle, WA, U.S.A. · School of Physics and Astronomy, University of Minnesota, Minneapolis, MN 55455, USA +6

  57. Can machine learning for quantum-gas experiments be explainable?

    May 18, 2026I. B. Spielman amd J. P. ZwolakInterpretable MLScientific ML

    National Institute of Standards and Technology, Gaithersburg, MD 20899, USA · Department of Physics, University of Maryland, College Park, MD 20742, USA · Joint Quantum Institute, University of Maryland, College Park, MD 20742, USA

  58. Buffer-Parameterized Machine Learning Surrogate Models for Cross-Technology Signal Integrity Analysis and Optimization

    May 18, 2026Julian Withöft, Werner John, Emre Ecik +2Neural Surrogate ModelingSurrogate-Assisted Optimization

    Information Processing Lab, Faculty for Electrical Engineering and Information Technology, TU Dortmund, Germany · Pyramide2525, Paderborn, Germany · EMC Technology Center Paderborn, Zuken GmbH, Paderborn, Germany

  59. Mechanism Learning: Prototype-Anchored Mechanism Inference for Scientific Forecasting

    May 16, 2026Qian Jiang, Liping SunPrototype-Based LearningNon-Stationary Time Series Forecasting

    School of Computing · The Australian National University · Canberra, ACT 2601, Australia +3

  60. CTF4Nuclear: Common Task Framework for Nuclear Fission and Fusion Models

    May 15, 2026Stefano Riva, Carolina Introini, Antonio Cammi +13Surrogate ModelingScientific ML

    Autodesk Research, London, UK · Department of Energy, Nuclear Engineering Division, Politecnico di Milano, Milan, Italy · Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139 +10