Alex Lamb
Alex Lamb
Université de Montréal, Google Brain, Amazon (formerly)
Verified email at amazon.com - Homepage
TitleCited byYear
Adversarially learned inference
V Dumoulin, I Belghazi, B Poole, O Mastropietro, A Lamb, M Arjovsky, ...
arXiv preprint arXiv:1606.00704, 2016
6022016
Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv preprint arXiv:1605.02688, 2016
5692016
Separating fact from fear: Tracking flu infections on twitter
A Lamb, MJ Paul, M Dredze
Proceedings of the 2013 Conference of the North American Chapter of the …, 2013
2352013
Professor Forcing: A New Algorithm for Training Recurrent Networks
A Goyal, A Lamb, Y Zhang, S Zhang, A Courville, Y Bengio
Neural Information Processing Systems (NIPS) 2016, 2016
208*2016
Discriminative Regularization for Generative Models
A Lamb, V Dumoulin, A Courville
DeepVision Workshop (CVPR), 2016
542016
Variance reduction in sgd by distributed importance sampling
G Alain, A Lamb, C Sankar, A Courville, Y Bengio
arXiv preprint arXiv:1511.06481, 2015
382015
Interpolation consistency training for semi-supervised learning
V Verma, A Lamb, J Kannala, Y Bengio, D Lopez-Paz
arXiv preprint arXiv:1903.03825, 2019
262019
Manifold mixup: Encouraging meaningful on-manifold interpolation as a regularizer
V Verma, A Lamb, C Beckham, A Courville, I Mitliagkis, Y Bengio
stat 1050, 13, 2018
232018
Deep learning for classical Japanese literature
T Clanuwat, M Bober-Irizar, A Kitamoto, A Lamb, K Yamamoto, D Ha
arXiv preprint arXiv:1812.01718, 2018
182018
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
182016
Manifold mixup: Better representations by interpolating hidden states
V Verma, A Lamb, C Beckham, A Najafi, I Mitliagkas, A Courville, ...
arXiv preprint arXiv:1806.05236, 2018
162018
Fortified networks: Improving the robustness of deep networks by modeling the manifold of hidden representations
A Lamb, J Binas, A Goyal, D Serdyuk, S Subramanian, I Mitliagkas, ...
arXiv preprint arXiv:1804.02485, 2018
132018
Manifold mixup: Learning better representations by interpolating hidden states
V Verma, A Lamb, C Beckham, A Najafi, A Courville, I Mitliagkas, ...
112018
Investigating twitter as a source for studying behavioral responses to epidemics
A Lamb, MJ Paul, M Dredze
2012 AAAI Fall Symposium Series, 2012
112012
Theano: A Python framework for fast computation of mathematical expressions. arXiv e-prints abs/1605.02688 (May 2016)
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
URL http://arxiv. org/abs/1605.02688, 2016
62016
Actual: Actor-critic under adversarial learning
A Goyal, NR Ke, A Lamb, RD Hjelm, C Pal, J Pineau, Y Bengio
arXiv preprint arXiv:1711.04755, 2017
42017
GibbsNet: Iterative adversarial inference for deep graphical models
AM Lamb, D Hjelm, Y Ganin, JP Cohen, AC Courville, Y Bengio
Advances in Neural Information Processing Systems, 5089-5098, 2017
42017
Adversarial Mixup Resynthesizers
C Beckham, S Honari, A Lamb, V Verma, F Ghadiri, RD Hjelm, C Pal
arXiv preprint arXiv:1903.02709, 2019
32019
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy
A Lamb, V Verma, J Kannala, Y Bengio
arXiv preprint arXiv:1906.06784, 2019
22019
GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning
V Verma, M Qu, A Lamb, Y Bengio, J Kannala, J Tang
arXiv preprint arXiv:1909.11715, 2019
12019
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Articles 1–20