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Stefano Ermon
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Cited by
Year
Generative adversarial imitation learning
J Ho, S Ermon
Advances in Neural Information Processing Systems, 4565-4573, 2016
19912016
Combining satellite imagery and machine learning to predict poverty
N Jean, M Burke, M Xie, WM Davis, DB Lobell, S Ermon
Science 353 (6301), 790-794, 2016
12172016
Pixeldefend: Leveraging generative models to understand and defend against adversarial examples
Y Song, T Kim, S Nowozin, S Ermon, N Kushman
arXiv preprint arXiv:1710.10766, 2017
6132017
Infovae: Balancing learning and inference in variational autoencoders
S Zhao, J Song, S Ermon
Proceedings of the aaai conference on artificial intelligence 33 (01), 5885-5892, 2019
513*2019
A dirt-t approach to unsupervised domain adaptation
R Shu, HH Bui, H Narui, S Ermon
arXiv preprint arXiv:1802.08735, 2018
4392018
Coupling between oxygen redox and cation migration explains unusual electrochemistry in lithium-rich layered oxides
WE Gent, K Lim, Y Liang, Q Li, T Barnes, SJ Ahn, KH Stone, M McIntire, ...
Nature communications 8 (1), 1-12, 2017
4022017
Generative modeling by estimating gradients of the data distribution
Y Song, S Ermon
Advances in Neural Information Processing Systems 32, 2019
3802019
Transfer learning from deep features for remote sensing and poverty mapping
M Xie, N Jean, M Burke, D Lobell, S Ermon
Thirtieth AAAI Conference on Artificial Intelligence, 2016
3732016
Deep gaussian process for crop yield prediction based on remote sensing data
J You, X Li, M Low, D Lobell, S Ermon
Thirty-First AAAI conference on artificial intelligence, 2017
3512017
Infogail: Interpretable imitation learning from visual demonstrations
Y Li, J Song, S Ermon
Advances in Neural Information Processing Systems 30, 2017
350*2017
Accurate uncertainties for deep learning using calibrated regression
V Kuleshov, N Fenner, S Ermon
International conference on machine learning, 2796-2804, 2018
3452018
On the opportunities and risks of foundation models
R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ...
arXiv preprint arXiv:2108.07258, 2021
2942021
Label-free supervision of neural networks with physics and domain knowledge
R Stewart, S Ermon
Thirty-First AAAI Conference on Artificial Intelligence, 2017
2802017
Score-based generative modeling through stochastic differential equations
Y Song, J Sohl-Dickstein, DP Kingma, A Kumar, S Ermon, B Poole
arXiv preprint arXiv:2011.13456, 2020
2682020
Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning
CS Ho, N Jean, CA Hogan, L Blackmon, SS Jeffrey, M Holodniy, N Banaei, ...
Nature communications 10 (1), 1-8, 2019
2672019
Closed-loop optimization of fast-charging protocols for batteries with machine learning
PM Attia, A Grover, N Jin, KA Severson, TM Markov, YH Liao, MH Chen, ...
Nature 578 (7795), 397-402, 2020
2602020
Mopo: Model-based offline policy optimization
T Yu, G Thomas, L Yu, S Ermon, JY Zou, S Levine, C Finn, T Ma
Advances in Neural Information Processing Systems 33, 14129-14142, 2020
2592020
A survey on behavior recognition using WiFi channel state information
S Yousefi, H Narui, S Dayal, S Ermon, S Valaee
IEEE Communications Magazine 55 (10), 98-104, 2017
2572017
Constructing unrestricted adversarial examples with generative models
Y Song, R Shu, N Kushman, S Ermon
Advances in Neural Information Processing Systems 31, 2018
211*2018
Graphite: Iterative generative modeling of graphs
A Grover, A Zweig, S Ermon
International conference on machine learning, 2434-2444, 2019
2072019
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