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Miles Cranmer

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Princeton University and Flatiron Institute

AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models

Oct 04, 2023
Francois Lanusse, Liam Parker, Siavash Golkar, Miles Cranmer, Alberto Bietti, Michael Eickenberg, Geraud Krawezik, Michael McCabe, Ruben Ohana, Mariel Pettee, Bruno Regaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

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Multiple Physics Pretraining for Physical Surrogate Models

Oct 04, 2023
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

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xVal: A Continuous Number Encoding for Large Language Models

Oct 04, 2023
Siavash Golkar, Mariel Pettee, Michael Eickenberg, Alberto Bietti, Miles Cranmer, Geraud Krawezik, Francois Lanusse, Michael McCabe, Ruben Ohana, Liam Parker, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

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Reusability report: Prostate cancer stratification with diverse biologically-informed neural architectures

Sep 28, 2023
Christian Pedersen, Tiberiu Tesileanu, Tinghui Wu, Siavash Golkar, Miles Cranmer, Zijun Zhang, Shirley Ho

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Symbolic Regression on FPGAs for Fast Machine Learning Inference

May 06, 2023
Ho Fung Tsoi, Adrian Alan Pol, Vladimir Loncar, Ekaterina Govorkova, Miles Cranmer, Sridhara Dasu, Peter Elmer, Philip Harris, Isobel Ojalvo, Maurizio Pierini

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Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl

May 05, 2023
Miles Cranmer

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Learning Integrable Dynamics with Action-Angle Networks

Nov 24, 2022
Ameya Daigavane, Arthur Kosmala, Miles Cranmer, Tess Smidt, Shirley Ho

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Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational Wave Population Study

Nov 15, 2022
David Ruhe, Kaze Wong, Miles Cranmer, Patrick Forré

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Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks

Nov 15, 2022
Ji Won Park, Simon Birrer, Madison Ueland, Miles Cranmer, Adriano Agnello, Sebastian Wagner-Carena, Philip J. Marshall, Aaron Roodman, the LSST Dark Energy Science Collaboration

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A Neural Network Subgrid Model of the Early Stages of Planet Formation

Nov 08, 2022
Thomas Pfeil, Miles Cranmer, Shirley Ho, Philip J. Armitage, Tilman Birnstiel, Hubert Klahr

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