Ho, Shirley

21 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 Lost in Latent Space: An Empirical Study of Latent Diffusion Models for Physics Emulation François Rozet, Ruben Ohana, Michael McCabe, Gilles Louppe, Francois Lanusse, Shirley Ho

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

ICMLW 2024 Fast-Forward FARGO: Accelerating Protoplanetary Disk Simulations with Limited Data Valentina Tardugno Poleo, David W Hogg, 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 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 Predicting the Initial Conditions of the Universe Using a Deterministic Neural Network Vaibhav Jindal, Albert Liang, Aarti Singh, Shirley Ho, Drew Jamieson

NeurIPSW 2023 Surrogate Modeling for Computationally Expensive Simulations of Supernovae in High-Resolution Galaxy Simulations Keiya Hirashima, Kana Moriwaki, Michiko S. Fujii, Yutaka Hirai, Takayuki R. Saitoh, Junichiro Makino, 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

NeurIPSW 2021 Searching for the Weirdest Stars: A Convolutional Autoencoder-Based Pipeline for Detecting Anomalous Periodic Variable Stars Ho-Sang Chan, Siu-Hei Cheung, Victoria Ashley Villar, Shirley Ho

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

ICML 2016 Estimating Cosmological Parameters from the Dark Matter Distribution Siamak Ravanbakhsh, Junier Oliva, Sebastian Fromenteau, Layne Price, Shirley Ho, Jeff Schneider, Barnabas Poczos

AISTATS 2015 Fast Function to Function Regression Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Hy Trac, Shirley Ho, Jeff G. Schneider

ICML 2015 Finding Galaxies in the Shadows of Quasars with Gaussian Processes Roman Garnett, Shirley Ho, Jeff Schneider

NeurIPS 2015 Optimal Ridge Detection Using Coverage Risk Yen-Chi Chen, Christopher R Genovese, Shirley Ho, Larry Wasserman