George Stein

According to our database, George Stein authored at least 12 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Geometric Framework for Understanding Memorization in Generative Models.

Brendan Leigh Ross, Hamidreza Kamkari, Tongzi Wu, Rasa Hosseinzadeh, Zhaoyan Liu, George Stein, Jesse C. Cresswell, Gabriel Loaiza-Ganem

CoRR, 2024

Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks.

Antoni Kowalczuk, Jan Dubinski, Atiyeh Ashari Ghomi, Yi Sui, George Stein, Jiapeng Wu, Jesse C. Cresswell, Franziska Boenisch, Adam Dziedzic

CoRR, 2024

TabPFGen - Tabular Data Generation with TabPFN.

Junwei Ma, Apoorv Dankar, George Stein, Guangwei Yu, Anthony L. Caterini

CoRR, 2024

Self-supervised Representation Learning from Random Data Projectors.

Yi Sui, Tongzi Wu, Jesse C. Cresswell, Ga Wu, George Stein, Xiao Shi Huang, Xiaochen Zhang, Maksims Volkovs

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models.

George Stein, Jesse C. Cresswell, Rasa Hosseinzadeh, Yi Sui, Brendan Leigh Ross, Valentin Villecroze, Zhaoyan Liu, Anthony L. Caterini, J. Eric T. Taylor, Gabriel Loaiza-Ganem

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series.

George Stein, Uros Seljak, Vanessa Böhm, G. Aldering, P. Antilogus, C. Aragon, S. Bailey, C. Baltay, Sébastien Bongard, K. Boone, C. Buton, Y. Copin, S. Dixon, Dominique Fouchez, Emmanuel Gangler, R. Gupta, B. Hayden, W. Hillebrandt, M. Karmen, A. G. Kim, M. Kowalski, D. Kusters, P. F. Leget, F. Mondon, J. Nordin, R. Pain, E. Pecontal, R. Pereira, S. Perlmutter, K. A. Ponder, D. Rabinowitz, M. Rigault, D. Rubin, K. Runge, C. Saunders, G. Smadja, N. Suzuki, C. Tao, Rollin C. Thomas, Maria Vincenzi

CoRR, 2022

2021

Self-supervised similarity search for large scientific datasets.

George Stein, Peter Harrington, Jacqueline Blaum, Tomislav Medan, Zarija Lukic

CoRR, 2021

Mining for strong gravitational lenses with self-supervised learning.

George Stein, Jacqueline Blaum, Peter Harrington, Tomislav Medan, Zarija Lukic

CoRR, 2021

Estimating Galactic Distances From Images Using Self-supervised Representation Learning.

Md. Abul Hayat, Peter Harrington, George Stein, Zarija Lukic, Mustafa Mustafa

CoRR, 2021

2020

Self-Supervised Representation Learning for Astronomical Images.

Md. Abul Hayat, George Stein, Peter Harrington, Zarija Lukic, Mustafa Mustafa

CoRR, 2020

Unsupervised in-distribution anomaly detection of new physics through conditional density estimation.

George Stein, Uros Seljak, Biwei Dai

CoRR, 2020

2018

A volumetric deep Convolutional Neural Network for simulation of dark matter halo catalogues.

Philippe Berger, George Stein

CoRR, 2018