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Laurent Dinh
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Cited by
Year
Density estimation using real nvp
L Dinh, J Sohl-Dickstein, S Bengio
arXiv preprint arXiv:1605.08803, 2016
22342016
Nice: Non-linear independent components estimation
L Dinh, D Krueger, Y Bengio
arXiv preprint arXiv:1410.8516, 2014
14332014
Predicting parameters in deep learning
M Denil, B Shakibi, L Dinh, MA Ranzato, N De Freitas
Advances in neural information processing systems 26, 2013
13012013
A recurrent latent variable model for sequential data
J Chung, K Kastner, L Dinh, K Goel, AC Courville, Y Bengio
Advances in neural information processing systems 28, 2015
11122015
Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv e-prints, arXiv: 1605.02688, 2016
8162016
Sharp minima can generalize for deep nets
L Dinh, R Pascanu, S Bengio, Y Bengio
International Conference on Machine Learning, 1019-1028, 2017
5152017
Theano: A Python framework for fast computation of mathematical expressions
TTD Team, R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, ...
arXiv preprint arXiv:1605.02688, 2016
2132016
Techniques for learning binary stochastic feedforward neural networks
T Raiko, M Berglund, G Alain, L Dinh
arXiv preprint arXiv:1406.2989, 2014
1192014
Videoflow: A flow-based generative model for video
M Kumar, M Babaeizadeh, D Erhan, C Finn, S Levine, L Dinh, D Kingma
arXiv preprint arXiv:1903.01434 2 (5), 3, 2019
1082019
Discrete flows: Invertible generative models of discrete data
D Tran, K Vafa, K Agrawal, L Dinh, B Poole
Advances in Neural Information Processing Systems 32, 2019
832019
Videoflow: A conditional flow-based model for stochastic video generation
M Kumar, M Babaeizadeh, D Erhan, C Finn, S Levine, L Dinh, D Kingma
arXiv preprint arXiv:1903.01434, 2019
702019
Supranormal renographic differential renal function in congenital hydronephrosis: fact, not artifact
G CAPOLICCHIO, R JEDNAK, L DINH, JLP SALLE, A BRZEZINSKI, ...
The Journal of urology 161 (4), 1290-1294, 1999
541999
Augmented normalizing flows: Bridging the gap between generative flows and latent variable models
CW Huang, L Dinh, A Courville
arXiv preprint arXiv:2002.07101, 2020
462020
Learning awareness models
B Amos, L Dinh, S Cabi, T Rothörl, SG Colmenarejo, A Muldal, T Erez, ...
arXiv preprint arXiv:1804.06318, 2018
422018
Theano: A Python framework for fast computation of mathematical expressions. arXiv
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv preprint arXiv:1605.02688, 2016
372016
Invertible convolutional flow
M Karami, D Schuurmans, J Sohl-Dickstein, L Dinh, D Duckworth
Advances in Neural Information Processing Systems 32, 2019
332019
A RAD approach to deep mixture models
L Dinh, J Sohl-Dickstein, H Larochelle, R Pascanu
arXiv preprint arXiv:1903.07714, 2019
322019
Deep independence network analysis of structural brain imaging: application to schizophrenia
E Castro, RD Hjelm, SM Plis, L Dinh, JA Turner, VD Calhoun
IEEE transactions on medical imaging 35 (7), 1729-1740, 2016
302016
Learnable explicit density for continuous latent space and variational inference
CW Huang, A Touati, L Dinh, M Drozdzal, M Havaei, L Charlin, ...
arXiv preprint arXiv:1710.02248, 2017
282017
Harm de Vries, David Warde-Farley, Dustin J
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, and …, 2016
282016
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