Charlie Frogner
Charlie Frogner
Verified email at mit.edu - Homepage
Title
Cited by
Cited by
Year
Learning with a Wasserstein loss
C Frogner, C Zhang, H Mobahi, M Araya-Polo, T Poggio
arXiv preprint arXiv:1506.05439, 2015
3212015
Automated fault detection without seismic processing
M Araya-Polo, T Dahlke, C Frogner, C Zhang, T Poggio, D Hohl
The Leading Edge 36 (3), 208-214, 2017
1552017
Machine-learning based automated fault detection in seismic traces
C Zhang, C Frogner, M Araya-Polo, D Hohl
76th EAGE Conference and Exhibition 2014 2014 (1), 1-5, 2014
552014
Predicting geological features in 3D seismic data
T Dahlke, M Araya-Polo, C Zhang, C Frogner, T Poggio
Advances in Neural Information Processing Systems (NIPS) 29, 2016
172016
Approximate inference with wasserstein gradient flows
C Frogner, T Poggio
International Conference on Artificial Intelligence and Statistics, 2581-2590, 2020
112020
Discovering Weakly-Interacting Factors in a Complex Stochastic Process.
C Frogner, A Pfeffer
NIPS, 481-488, 2007
112007
Learning with a Wasserstein Loss Advances in Neural Information Processing Systems (NIPS)
C Frogner, C Zhang, H Mobahi, M Araya-Polo, T Poggio
72015
Learning entropic wasserstein embeddings
C Frogner, F Mirzazadeh, J Solomon
International Conference on Learning Representations (ICLR), 2019
52019
Incorporating unlabeled data into distributionally robust learning
C Frogner, S Claici, E Chien, J Solomon
arXiv preprint arXiv:1912.07729, 2019
42019
Fast and flexible inference of joint distributions from their marginals
C Frogner, T Poggio
International Conference on Machine Learning, 2002-2011, 2019
42019
Learning embeddings into entropic wasserstein spaces
C Frogner, F Mirzazadeh, J Solomon
arXiv preprint arXiv:1905.03329, 2019
32019
Heuristics for Automatically Decomposing a Stochastic Process for Factored Inference
C Frogner, A Pfeffer
2007
Regularized Least Squares
C Frogner
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Articles 1–13