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George Stein
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2020 – today
- 2024
- [c2]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 - [i11]Junwei Ma, Apoorv Dankar, George Stein, Guangwei Yu, Anthony L. Caterini:
TabPFGen - Tabular Data Generation with TabPFN. CoRR abs/2406.05216 (2024) - [i10]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 abs/2407.12588 (2024) - 2023
- [c1]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 - [i9]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 abs/2306.04675 (2023) - [i8]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 abs/2310.07756 (2023) - 2022
- [i7]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:
A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series. CoRR abs/2207.07645 (2022) - 2021
- [i6]Md. Abul Hayat, Peter Harrington, George Stein, Zarija Lukic, Mustafa Mustafa:
Estimating Galactic Distances From Images Using Self-supervised Representation Learning. CoRR abs/2101.04293 (2021) - [i5]George Stein
, Jacqueline Blaum, Peter Harrington, Tomislav Medan, Zarija Lukic:
Mining for strong gravitational lenses with self-supervised learning. CoRR abs/2110.00023 (2021) - [i4]George Stein, Peter Harrington, Jacqueline Blaum, Tomislav Medan, Zarija Lukic:
Self-supervised similarity search for large scientific datasets. CoRR abs/2110.13151 (2021) - 2020
- [i3]George Stein, Uros Seljak, Biwei Dai:
Unsupervised in-distribution anomaly detection of new physics through conditional density estimation. CoRR abs/2012.11638 (2020) - [i2]Md. Abul Hayat, George Stein, Peter Harrington, Zarija Lukic, Mustafa Mustafa:
Self-Supervised Representation Learning for Astronomical Images. CoRR abs/2012.13083 (2020)
2010 – 2019
- 2018
- [i1]Philippe Berger, George Stein
:
A volumetric deep Convolutional Neural Network for simulation of dark matter halo catalogues. CoRR abs/1805.04537 (2018)
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