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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
Advances in Neural Information Processing Systems 2015, 2015
6852015
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
2942017
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
1042014
Learning embeddings into entropic wasserstein spaces
C Frogner, F Mirzazadeh, J Solomon
International Conference on Learning Representations (ICLR), 2019
47*2019
Approximate inference with Wasserstein gradient flows
C Frogner, T Poggio
International Conference on Artificial Intelligence and Statistics, 2581-2590, 2020
302020
Incorporating unlabeled data into distributionally robust learning
C Frogner, S Claici, E Chien, J Solomon
Journal of Machine Learning Research 22 (56), 1-46, 2021
252021
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
202016
Fast and flexible inference of joint distributions from their marginals
C Frogner, T Poggio
International Conference on Machine Learning, 2002-2011, 2019
162019
Discovering weakly-interacting factors in a complex stochastic process
C Frogner, A Pfeffer
Advances in Neural Information Processing Systems 20, 2007
112007
Machine-learning based automated fault detection in seismic traces: 76th Conference and Exhibition, EAGE
C Zhang, C Frogner, M Araya-Polo, D Hohl
Extended Abstracts, http://dx. doi. org/10.3997/2214-4609.20141500, 2014
92014
Support Vector Machines
C Frogner
MIT, 2011
22011
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