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Mohammad Pezeshki
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2020 – today
- 2023
- [i14]Pascal Tikeng Notsawo Jr., Hattie Zhou, Mohammad Pezeshki, Irina Rish, Guillaume Dumas:
Predicting Grokking Long Before it Happens: A look into the loss landscape of models which grok. CoRR abs/2306.13253 (2023) - [i13]Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz:
Discovering environments with XRM. CoRR abs/2309.16748 (2023) - [i12]Reyhane Askari Hemmat, Mohammad Pezeshki, Florian Bordes, Michal Drozdzal, Adriana Romero-Soriano:
Feedback-guided Data Synthesis for Imbalanced Classification. CoRR abs/2310.00158 (2023) - 2022
- [c8]Badr Youbi Idrissi, Martín Arjovsky, Mohammad Pezeshki, David Lopez-Paz:
Simple data balancing achieves competitive worst-group-accuracy. CLeaR 2022: 336-351 - [c7]Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie:
Multi-scale Feature Learning Dynamics: Insights for Double Descent. ICML 2022: 17669-17690 - 2021
- [c6]Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie:
Gradient Starvation: A Learning Proclivity in Neural Networks. NeurIPS 2021: 1256-1272 - [i11]Badr Youbi Idrissi, Martín Arjovsky, Mohammad Pezeshki, David Lopez-Paz:
Simple data balancing achieves competitive worst-group-accuracy. CoRR abs/2110.14503 (2021) - [i10]Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie:
Multi-scale Feature Learning Dynamics: Insights for Double Descent. CoRR abs/2112.03215 (2021) - 2020
- [i9]Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie:
Gradient Starvation: A Learning Proclivity in Neural Networks. CoRR abs/2011.09468 (2020)
2010 – 2019
- 2019
- [c5]Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Rémi Le Priol, Gabriel Huang, Simon Lacoste-Julien, Ioannis Mitliagkas:
Negative Momentum for Improved Game Dynamics. AISTATS 2019: 1802-1811 - 2018
- [i8]Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Gabriel Huang, Rémi Le Priol, Simon Lacoste-Julien, Ioannis Mitliagkas:
Negative Momentum for Improved Game Dynamics. CoRR abs/1807.04740 (2018) - [i7]Remi Tachet des Combes, Mohammad Pezeshki, Samira Shabanian, Aaron C. Courville, Yoshua Bengio:
On the Learning Dynamics of Deep Neural Networks. CoRR abs/1809.06848 (2018) - 2017
- [c4]David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron C. Courville, Christopher J. Pal:
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. ICLR (Poster) 2017 - [i6]Ying Zhang, Mohammad Pezeshki, Philemon Brakel, Saizheng Zhang, César Laurent, Yoshua Bengio, Aaron C. Courville:
Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks. CoRR abs/1701.02720 (2017) - 2016
- [c3]Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron C. Courville, Yoshua Bengio:
Deconstructing the Ladder Network Architecture. ICML 2016: 2368-2376 - [c2]Ying Zhang, Mohammad Pezeshki, Philémon Brakel, Saizheng Zhang, César Laurent, Yoshua Bengio, Aaron C. Courville:
Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks. INTERSPEECH 2016: 410-414 - [i5]Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang:
Theano: A Python framework for fast computation of mathematical expressions. CoRR abs/1605.02688 (2016) - [i4]David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Aaron C. Courville, Chris Pal:
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. CoRR abs/1606.01305 (2016) - 2015
- [i3]Mohammad Pezeshki:
Sequence Modeling using Gated Recurrent Neural Networks. CoRR abs/1501.00299 (2015) - [i2]Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron C. Courville, Yoshua Bengio:
Deconstructing the Ladder Network Architecture. CoRR abs/1511.06430 (2015) - 2014
- [c1]Mohammad Ali Keyvanrad, Mohammad Pezeshki, Mohammad Ali Homayounpour:
Deep Belief Networks for Image Denoising. ICLR (Workshop Poster) 2014 - 2013
- [i1]Mohammad Pezeshki, Sajjad Gholami, Ahmad Nickabadi:
Distinction between features extracted using deep belief networks. CoRR abs/1312.6157 (2013)
Coauthor Index
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