George Stein

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 13

Top Topics

Convolutional Neural Network

Diffusion Models

Conditional Density Estimation

Top Venues

Publications

Antoni Kowalczuk, Jan Dubinski, Atiyeh Ashari Ghomi, Yi Sui, George Stein, Jiapeng Wu, Jesse C. Cresswell, Franziska Boenisch, Adam Dziedzic
Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks. CoRR (2024)
Junwei Ma, Apoorv Dankar, George Stein, Guangwei Yu, Anthony L. Caterini
TabPFGen - Tabular Data Generation with TabPFN. CoRR (2024)
Yi Sui, Tongzi Wu, Jesse C. Cresswell, Ga Wu, George Stein, Xiao Shi Huang, Xiaochen Zhang, Maksims Volkovs
Self-supervised Representation Learning from Random Data Projectors. ICLR (2024)
Yi Sui, Tongzi Wu, Jesse C. Cresswell, Ga Wu, George Stein, Xiao Shi Huang, Xiaochen Zhang, Maksims Volkovs
Self-supervised Representation Learning From Random Data Projectors. CoRR (2023)
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
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models. NeurIPS (2023)
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
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models. CoRR (2023)
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, R. C. Thomas, M. Vincenzi
A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series. CoRR (2022)
George Stein, Peter Harrington, Jacqueline Blaum, Tomislav Medan, Zarija Lukic
Self-supervised similarity search for large scientific datasets. CoRR (2021)
Md Abul Hayat, Peter Harrington, George Stein, Zarija Lukic, Mustafa Mustafa
Estimating Galactic Distances From Images Using Self-supervised Representation Learning. CoRR (2021)
George Stein, Jacqueline Blaum, Peter Harrington, Tomislav Medan, Zarija Lukic
Mining for strong gravitational lenses with self-supervised learning. CoRR (2021)
Md Abul Hayat, George Stein, Peter Harrington, Zarija Lukic, Mustafa Mustafa
Self-Supervised Representation Learning for Astronomical Images. CoRR (2020)
George Stein, Uros Seljak, Biwei Dai
Unsupervised in-distribution anomaly detection of new physics through conditional density estimation. CoRR (2020)
Philippe Berger, George Stein
A volumetric deep Convolutional Neural Network for simulation of dark matter halo catalogues. CoRR (2018)