Scientific ML

ML: Machine Learning

Ask about this topic

Momentum

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

Jul 13Week of Sep 28
View on map

Latest papers 82

All topics
CardsList

  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.