Cranmer, Miles

17 publications

NeurIPS 2025 AION-1: Omnimodal Foundation Model for Astronomical Sciences Liam Holden Parker, Francois Lanusse, Jeff Shen, Ollie Liu, Tom Hehir, Leopoldo Sarra, Lucas Thibaut Meyer, Micah Bowles, Sebastian Wagner-Carena, Helen Qu, Siavash Golkar, Alberto Bietti, Hatim Bourfoune, Pierre Cornette, Keiya Hirashima, Geraud Krawezik, Ruben Ohana, Nicholas Lourie, Michael McCabe, Rudy Morel, Payel Mukhopadhyay, Mariel Pettee, Kyunghyun Cho, Miles Cranmer, Shirley Ho

NeurIPS 2025 Common Task Framework for a Critical Evaluation of Scientific Machine Learning Algorithms Philippe Martin Wyder, Judah A Goldfeder, Alexey Yermakov, Yue Zhao, Stefano Riva, Jan P. Williams, David Zoro, Amy Sara Rude, Matteo Tomasetto, Joe Germany, Joseph Bakarji, Georg Maierhofer, Miles Cranmer, J. Nathan Kutz

ICLRW 2025 Compute-Adaptive Surrogate Modeling of Partial Differential Equations Payel Mukhopadhyay, Michael McCabe, Ruben Ohana, Miles Cranmer

TMLR 2025 Machine Learning with Physics Knowledge for Prediction: A Survey Joe Watson, Chen Song, Oliver Weeger, Theo Gruner, An Thai Le, Kay Hansel, Ahmed Hendawy, Oleg Arenz, Will Trojak, Miles Cranmer, Carlo D'Eramo, Fabian Buelow, Tanmay Goyal, Jan Peters, Martin W Hoffmann

NeurIPS 2025 Predicting Partially Observable Dynamical Systems via Diffusion Models with a Multiscale Inference Scheme Rudy Morel, Francesco Pio Ramunno, Jeff Shen, Alberto Bietti, Kyunghyun Cho, Miles Cranmer, Siavash Golkar, Olexandr Gugnin, Geraud Krawezik, Tanya Marwah, Michael McCabe, Lucas Thibaut Meyer, Payel Mukhopadhyay, Ruben Ohana, Liam Holden Parker, Helen Qu, François Rozet, K.D. Leka, Francois Lanusse, David Fouhey, Shirley Ho

NeurIPS 2024 Multiple Physics Pretraining for Spatiotemporal Surrogate Models Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Parker, Ruben Ohana, Miles Cranmer, Alberto Bietti, Michael Eickenberg, Siavash Golkar, Geraud Krawezik, Francois Lanusse, Mariel Pettee, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

NeurIPS 2024 Symbolic Regression with a Learned Concept Library Arya Grayeli, Atharva Sehgal, Omar Costilla-Reyes, Miles Cranmer, Swarat Chaudhuri

ICMLW 2024 Symbolic Regression with a Learned Concept Library Arya Grayeli, Atharva Sehgal, Omar Costilla Reyes, Miles Cranmer, Swarat Chaudhuri

NeurIPS 2024 The Multimodal Universe: Enabling Large-Scale Machine Learning with 100 TB of Astronomical Scientific Data Eirini Angeloudi, Jeroen Audenaert, Micah Bowles, Benjamin M. Boyd, David Chemaly, Brian Cherinka, Ioana Ciucă, Miles Cranmer, Aaron Do, Matthew Grayling, Erin E. Hayes, Tom Hehir, Shirley Ho, Marc Huertas-Company, Kartheik G. Iyer, Maja Jablonska, Francois Lanusse, Henry W. Leung, Kaisey Mandel, Juan Rafael Martínez-Galarza, Peter Melchior, Lucas Meyer, Liam H. Parker, Helen Qu, Jeff Shen, Michael J. Smith, Connor Stone, Mike Walmsley, John F. Wu

NeurIPS 2024 The Well: A Large-Scale Collection of Diverse Physics Simulations for Machine Learning Ruben Ohana, Michael McCabe, Lucas Meyer, Rudy Morel, Fruzsina J. Agocs, Miguel Beneitez, Marsha Berger, Blakesley Burkhart, Stuart B. Dalziel, Drummond B. Fielding, Daniel Fortunato, Jared A. Goldberg, Keiya Hirashima, Yan-Fei Jiang, Rich R. Kerswell, Suryanarayana Maddu, Jonah Miller, Payel Mukhopadhyay, Stefan S. Nixon, Jeff Shen, Romain Watteaux, Bruno Régaldo-Saint Blancard, François Rozet, Liam H. Parker, Miles Cranmer, Shirley Ho

NeurIPSW 2024 The Well: A Large-Scale Collection of Diverse Physics Simulations for Machine Learning Ruben Ohana, Michael McCabe, Lucas Thibaut Meyer, Rudy Morel, Fruzsina Julia Agocs, Miguel Beneitez, Marsha Berger, Blakesley Burkhart, Stuart B. Dalziel, Drummond Buschman Fielding, Daniel Fortunato, Jared A. Goldberg, Keiya Hirashima, Yan-Fei Jiang, Rich Kerswell, Suryanarayana Maddu, Jonah M. Miller, Payel Mukhopadhyay, Stefan S. Nixon, Jeff Shen, Romain Watteaux, Bruno Régaldo-Saint Blancard, Liam Holden Parker, Miles Cranmer, Shirley Ho

NeurIPSW 2023 AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models Francois Lanusse, Liam Holden Parker, Siavash Golkar, Alberto Bietti, Miles Cranmer, Michael Eickenberg, Geraud Krawezik, Michael McCabe, Ruben Ohana, Mariel Pettee, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

NeurIPSW 2023 Multiple Physics Pretraining for Physical Surrogate Models Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Holden Parker, Ruben Ohana, Miles Cranmer, Alberto Bietti, Michael Eickenberg, Siavash Golkar, Geraud Krawezik, Francois Lanusse, Mariel Pettee, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

NeurIPSW 2023 xVal: A Continuous Number Encoding for Large Language Models Siavash Golkar, Mariel Pettee, Michael Eickenberg, Alberto Bietti, Miles Cranmer, Geraud Krawezik, Francois Lanusse, Michael McCabe, Ruben Ohana, Liam Holden Parker, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

ICLR 2022 Learned Simulators for Turbulence Kim Stachenfeld, Drummond Buschman Fielding, Dmitrii Kochkov, Miles Cranmer, Tobias Pfaff, Jonathan Godwin, Can Cui, Shirley Ho, Peter Battaglia, Alvaro Sanchez-Gonzalez

NeurIPS 2020 Discovering Symbolic Models from Deep Learning with Inductive Biases Miles Cranmer, Alvaro Sanchez Gonzalez, Peter Battaglia, Rui Xu, Kyle Cranmer, David Spergel, Shirley Ho

ICLRW 2020 Lagrangian Neural Networks Miles Cranmer, Sam Greydanus, Stephan Hoyer, Peter Battaglia, David Spergel, Shirley Ho