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2020 – today
- 2024
[j5]Mehrzad Shahinmoghadam
, Samira Ebrahimi Kahou, Ali Motamedi:
Neural semantic tagging for natural language-based search in building information models: Implications for practice. Comput. Ind. 155: 104063 (2024)- [j4]Patrik Joslin Kenfack, Samira Ebrahimi Kahou, Ulrich Aïvodji:
A Survey on Fairness Without Demographics. Trans. Mach. Learn. Res. 2024 (2024) - [c27]Pranav Agarwal, Sheldon Andrews, Samira Ebrahimi Kahou:
Learning to Play Atari in a World of Tokens. ICML 2024 - [i39]Jordi Armengol-Estapé, Vincent Michalski, Ramnath Kumar, Pierre-Luc St-Charles, Doina Precup, Samira Ebrahimi Kahou:
On the Limits of Multi-modal Meta-Learning with Auxiliary Task Modulation Using Conditional Batch Normalization. CoRR abs/2405.18751 (2024) - [i38]Pranav Agarwal, Sheldon Andrews, Samira Ebrahimi Kahou:
Learning to Play Atari in a World of Tokens. CoRR abs/2406.01361 (2024) - [i37]Jithendaraa Subramanian, Shivakanth Sujit, Niloy Irtisam, Umong Sain, Derek Nowrouzezahrai, Samira Ebrahimi Kahou, Riashat Islam:
Reinforcement Learning for Sequence Design Leveraging Protein Language Models. CoRR abs/2407.03154 (2024) - [i36]Aamer Abdul Rahman, Pranav Agarwal, Rita Noumeir, Philippe Jouvet, Vincent Michalski, Samira Ebrahimi Kahou:
Empowering Clinicians with Medical Decision Transformers: A Framework for Sepsis Treatment. CoRR abs/2407.19380 (2024) - [i35]Abdalwhab Abdalwhab, Giovanni Beltrame, Samira Ebrahimi Kahou, David St-Onge:
Learning Multi-agent Multi-machine Tending by Mobile Robots. CoRR abs/2408.16875 (2024) - 2023
- [j3]Imen Trabelsi, Manel Abdellatif, Abdalgader Abubaker, Naouel Moha, Sébastien Mosser, Samira Ebrahimi Kahou, Yann-Gaël Guéhéneuc:
From legacy to microservices: A type-based approach for microservices identification using machine learning and semantic analysis. J. Softw. Evol. Process. 35(10) (2023) - [j2]Shivakanth Sujit, Pedro H. M. Braga, Jörg Bornschein, Samira Ebrahimi Kahou:
Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies. Trans. Mach. Learn. Res. 2023 (2023) - [c26]Somjit Nath, Gopeshh Raaj Subbaraj, Khimya Khetarpal, Samira Ebrahimi Kahou:
Discovering Object-Centric Generalized Value Functions From Pixels. ICML 2023: 25755-25768 - [c25]Ivaxi Sheth, Pedro H. M. Braga, Shivakanth Sujit, Sahar Dastani, Samira Ebrahimi Kahou:
RelationalUNet for Image Segmentation. MLMI@MICCAI (1) 2023: 320-329 - [c24]Ivaxi Sheth, Samira Ebrahimi Kahou:
Auxiliary Losses for Learning Generalizable Concept-based Models. NeurIPS 2023 - [c23]Shivakanth Sujit, Somjit Nath, Pedro H. M. Braga, Samira Ebrahimi Kahou:
Prioritizing Samples in Reinforcement Learning with Reducible Loss. NeurIPS 2023 - [i34]Laya Rafiee Sevyeri, Ivaxi Sheth, Farhood Farahnak, Alexandre See, Samira Ebrahimi Kahou, Thomas Fevens, Mohammad Havaei:
Source-free Domain Adaptation Requires Penalized Diversity. CoRR abs/2304.02798 (2023) - [i33]Somjit Nath, Gopeshh Raaj Subbaraj, Khimya Khetarpal, Samira Ebrahimi Kahou:
Discovering Object-Centric Generalized Value Functions From Pixels. CoRR abs/2304.13892 (2023) - [i32]Nikunj Gupta, Samira Ebrahimi Kahou:
CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning. CoRR abs/2306.11128 (2023) - [i31]Pranav Agarwal, Aamer Abdul Rahman, Pierre-Luc St-Charles, Simon J. D. Prince, Samira Ebrahimi Kahou:
Transformers in Reinforcement Learning: A Survey. CoRR abs/2307.05979 (2023) - [i30]Patrik Joslin Kenfack, Samira Ebrahimi Kahou, Ulrich Aïvodji:
Fairness Under Demographic Scarce Regime. CoRR abs/2307.13081 (2023) - [i29]Ivaxi Sheth, Samira Ebrahimi Kahou:
Auxiliary Losses for Learning Generalizable Concept-based Models. CoRR abs/2311.11108 (2023) - [i28]Sacha Morin, Somjit Nath, Samira Ebrahimi Kahou, Guy Wolf:
Spectral Temporal Contrastive Learning. CoRR abs/2312.00966 (2023) - 2022
- [c22]Moslem Yazdanpanah, Aamer Abdul Rahman, Muawiz Chaudhary, Christian Desrosiers, Mohammad Havaei, Eugene Belilovsky, Samira Ebrahimi Kahou:
Revisiting Learnable Affines for Batch Norm in Few-Shot Transfer Learning. CVPR 2022: 9099-9108 - [c21]Roger Girgis, Florian Golemo, Felipe Codevilla, Martin Weiss, Jim Aldon D'Souza, Samira Ebrahimi Kahou, Felix Heide, Christopher Pal:
Latent Variable Sequential Set Transformers for Joint Multi-Agent Motion Prediction. ICLR 2022 - [c20]Arnav Kumar Jain, Shivakanth Sujit, Shruti Joshi, Vincent Michalski, Danijar Hafner, Samira Ebrahimi Kahou:
Learning Robust Dynamics through Variational Sparse Gating. NeurIPS 2022 - [i27]Fereshteh Shakeri, Malik Boudiaf, Sina Mohammadi, Ivaxi Sheth, Mohammad Havaei, Ismail Ben Ayed, Samira Ebrahimi Kahou:
FHIST: A Benchmark for Few-shot Classification of Histological Images. CoRR abs/2206.00092 (2022) - [i26]Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou:
Latent Variable Models for Bayesian Causal Discovery. CoRR abs/2207.05723 (2022) - [i25]Shivakanth Sujit, Somjit Nath, Pedro H. M. Braga, Samira Ebrahimi Kahou:
Prioritizing Samples in Reinforcement Learning with Reducible Loss. CoRR abs/2208.10483 (2022) - [i24]Somjit Nath, Samira Ebrahimi Kahou:
Locally Constrained Representations in Reinforcement Learning. CoRR abs/2209.09441 (2022) - [i23]Arnav Kumar Jain, Shivakanth Sujit, Shruti Joshi, Vincent Michalski, Danijar Hafner, Samira Ebrahimi Kahou:
Learning Robust Dynamics through Variational Sparse Gating. CoRR abs/2210.11698 (2022) - [i22]Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Nan Rosemary Ke, Tristan Deleu, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou:
Learning Latent Structural Causal Models. CoRR abs/2210.13583 (2022) - [i21]Mohsen Fayyaz, Ehsan Aghazadeh, Ali Modarressi, Mohammad Taher Pilehvar, Yadollah Yaghoobzadeh, Samira Ebrahimi Kahou:
BERT on a Data Diet: Finding Important Examples by Gradient-Based Pruning. CoRR abs/2211.05610 (2022) - [i20]Pranav Agarwal, Marek Teichmann, Sheldon Andrews, Samira Ebrahimi Kahou:
Automatic Evaluation of Excavator Operators using Learned Reward Functions. CoRR abs/2211.07941 (2022) - [i19]Ivaxi Sheth, Aamer Abdul Rahman, Mohammad Havaei, Samira Ebrahimi Kahou:
Pitfalls of Conditional Batch Normalization for Contextual Multi-Modal Learning. CoRR abs/2211.15071 (2022) - [i18]Shivakanth Sujit, Pedro H. M. Braga, Jörg Bornschein, Samira Ebrahimi Kahou:
Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies. CoRR abs/2212.08131 (2022) - 2021
- [c19]Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Nazanin Mohammadi Sepahvand, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent:
Accounting for Variance in Machine Learning Benchmarks. MLSys 2021 - [i17]Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Naz Sepah, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Dmitriy Serdyuk, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent:
Accounting for Variance in Machine Learning Benchmarks. CoRR abs/2103.03098 (2021) - [i16]Roger Girgis, Florian Golemo, Felipe Codevilla, Jim Aldon D'Souza, Samira Ebrahimi Kahou, Felix Heide, Christopher J. Pal:
Latent Variable Nested Set Transformers & AutoBots. CoRR abs/2104.00563 (2021) - [i15]David Kanaa, Vikram Voleti, Samira Ebrahimi Kahou, Christopher Pal:
Simple Video Generation using Neural ODEs. CoRR abs/2109.03292 (2021) - 2020
- [c18]Md Rifat Arefin, Vincent Michalski, Pierre-Luc St-Charles, Alfredo Kalaitzis, Sookyung Kim, Samira Ebrahimi Kahou, Yoshua Bengio:
Multi-Image Super-Resolution for Remote Sensing using Deep Recurrent Networks. CVPR Workshops 2020: 816-825 - [i14]Michel Deudon, Alfredo Kalaitzis, Israel Goytom, Md Rifat Arefin, Zhichao Lin, Kris Sankaran, Vincent Michalski, Samira Ebrahimi Kahou, Julien Cornebise, Yoshua Bengio:
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery. CoRR abs/2002.06460 (2020) - [i13]Hadia Mohmmed Osman Ahmed Samil, Annabelle Martin, Arnav Kumar Jain, Susan Amin, Samira Ebrahimi Kahou:
Predicting Regional Locust Swarm Distribution with Recurrent Neural Networks. CoRR abs/2011.14371 (2020)
2010 – 2019
- 2019
- [c17]Sarath Chandar, Chinnadhurai Sankar, Eugene Vorontsov, Samira Ebrahimi Kahou, Yoshua Bengio:
Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies. AAAI 2019: 3280-3287 - [c16]Martin Weiss, Simon Chamorro, Roger Girgis, Margaux Luck, Samira Ebrahimi Kahou, Joseph Paul Cohen, Derek Nowrouzezahrai, Doina Precup, Florian Golemo, Chris Pal:
Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments. CoRL 2019: 1314-1327 - [c15]Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz, R. Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio, Graham W. Taylor:
Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction. ICCV 2019: 10303-10311 - [c14]Mehdi Fatemi, Shikhar Sharma, Harm van Seijen, Samira Ebrahimi Kahou:
Dead-ends and Secure Exploration in Reinforcement Learning. ICML 2019: 1873-1881 - [c13]Sookyung Kim, Hyojin Kim, Joonseok Lee, Sangwoong Yoon, Samira Ebrahimi Kahou, Karthik Kashinath, Prabhat:
Deep-Hurricane-Tracker: Tracking and Forecasting Extreme Climate Events. WACV 2019: 1761-1769 - [i12]Sarath Chandar, Chinnadhurai Sankar, Eugene Vorontsov, Samira Ebrahimi Kahou, Yoshua Bengio:
Towards Non-saturating Recurrent Units for Modelling Long-term Dependencies. CoRR abs/1902.06704 (2019) - [i11]Vincent Michalski, Vikram Voleti, Samira Ebrahimi Kahou, Anthony Ortiz, Pascal Vincent, Chris Pal, Doina Precup:
An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation. CoRR abs/1908.00061 (2019) - [i10]Martin Weiss, Simon Chamorro, Roger Girgis, Margaux Luck, Samira Ebrahimi Kahou, Joseph Paul Cohen, Derek Nowrouzezahrai, Doina Precup, Florian Golemo, Chris Pal:
Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments. CoRR abs/1910.13249 (2019) - 2018
- [c12]Samira Ebrahimi Kahou, Vincent Michalski, Adam Atkinson, Ákos Kádár, Adam Trischler, Yoshua Bengio:
FigureQA: An Annotated Figure Dataset for Visual Reasoning. ICLR (Workshop) 2018 - [c11]Shikhar Sharma, Dendi Suhubdy, Vincent Michalski, Samira Ebrahimi Kahou, Yoshua Bengio:
ChatPainter: Improving Text to Image Generation using Dialogue. ICLR (Workshop) 2018 - [c10]Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, Chris Pal:
Towards Deep Conversational Recommendations. NeurIPS 2018: 9748-9758 - [i9]Shikhar Sharma, Dendi Suhubdy, Vincent Michalski, Samira Ebrahimi Kahou, Yoshua Bengio:
ChatPainter: Improving Text to Image Generation using Dialogue. CoRR abs/1802.08216 (2018) - [i8]Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz, R. Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio, Graham W. Taylor:
Keep Drawing It: Iterative language-based image generation and editing. CoRR abs/1811.09845 (2018) - [i7]Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, Chris Pal:
Towards Deep Conversational Recommendations. CoRR abs/1812.07617 (2018) - 2017
- [c9]Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic, Christopher Joseph Pal, Pascal Vincent:
RATM: Recurrent Attentive Tracking Model. CVPR Workshops 2017: 1613-1622 - [c8]Raghav Goyal, Samira Ebrahimi Kahou, Vincent Michalski, Joanna Materzynska, Susanne Westphal, Heuna Kim, Valentin Haenel, Ingo Fründ, Peter Yianilos, Moritz Mueller-Freitag, Florian Hoppe, Christian Thurau, Ingo Bax, Roland Memisevic:
The "Something Something" Video Database for Learning and Evaluating Visual Common Sense. ICCV 2017: 5843-5851 - [c7]Gregor Urban, Krzysztof J. Geras, Samira Ebrahimi Kahou, Özlem Aslan, Shengjie Wang, Abdelrahman Mohamed, Matthai Philipose, Matthew Richardson, Rich Caruana:
Do Deep Convolutional Nets Really Need to be Deep and Convolutional? ICLR (Poster) 2017 - [c6]Evan Racah, Christopher Beckham, Tegan Maharaj, Samira Ebrahimi Kahou, Prabhat, Chris Pal:
ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events. NIPS 2017: 3402-3413 - [i6]Raghav Goyal, Samira Ebrahimi Kahou, Vincent Michalski, Joanna Materzynska, Susanne Westphal, Heuna Kim, Valentin Haenel, Ingo Fründ, Peter Yianilos, Moritz Mueller-Freitag, Florian Hoppe, Christian Thurau, Ingo Bax, Roland Memisevic:
The "something something" video database for learning and evaluating visual common sense. CoRR abs/1706.04261 (2017) - [i5]Samira Ebrahimi Kahou, Adam Atkinson, Vincent Michalski, Ákos Kádár, Adam Trischler, Yoshua Bengio:
FigureQA: An Annotated Figure Dataset for Visual Reasoning. CoRR abs/1710.07300 (2017) - 2016
- [j1]Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre, Vincent Michalski, Kishore Konda, Sébastien Jean, Pierre Froumenty, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Raul Chandias Ferrari, Mehdi Mirza, David Warde-Farley, Aaron C. Courville, Pascal Vincent, Roland Memisevic, Christopher Joseph Pal, Yoshua Bengio:
EmoNets: Multimodal deep learning approaches for emotion recognition in video. J. Multimodal User Interfaces 10(2): 99-111 (2016) - [i4]Gregor Urban, Krzysztof J. Geras, Samira Ebrahimi Kahou, Özlem Aslan, Shengjie Wang, Rich Caruana, Abdelrahman Mohamed, Matthai Philipose, Matthew Richardson:
Do Deep Convolutional Nets Really Need to be Deep (Or Even Convolutional)? CoRR abs/1603.05691 (2016) - [i3]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) - 2015
- [c5]Samira Ebrahimi Kahou, Vincent Michalski, Kishore Reddy Konda, Roland Memisevic, Christopher Joseph Pal:
Recurrent Neural Networks for Emotion Recognition in Video. ICMI 2015: 467-474 - [c4]Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, Yoshua Bengio:
FitNets: Hints for Thin Deep Nets. ICLR (Poster) 2015 - [i2]Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre, Vincent Michalski, Kishore Reddy Konda, Sébastien Jean, Pierre Froumenty, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Raul Chandias Ferrari, Mehdi Mirza, David Warde-Farley, Aaron C. Courville, Pascal Vincent, Roland Memisevic, Christopher J. Pal, Yoshua Bengio:
EmoNets: Multimodal deep learning approaches for emotion recognition in video. CoRR abs/1503.01800 (2015) - [i1]Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic:
RATM: Recurrent Attentive Tracking Model. CoRR abs/1510.08660 (2015) - 2014
- [c3]Samira Ebrahimi Kahou, Pierre Froumenty, Christopher J. Pal:
Facial Expression Analysis Based on High Dimensional Binary Features. ECCV Workshops (2) 2014: 135-147 - 2013
- [c2]Samira Ebrahimi Kahou, Christopher J. Pal, Xavier Bouthillier, Pierre Froumenty, Çaglar Gülçehre, Roland Memisevic, Pascal Vincent, Aaron C. Courville, Yoshua Bengio, Raul Chandias Ferrari, Mehdi Mirza, Sébastien Jean, Pierre Luc Carrier, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Abhishek Aggarwal, Jeremie Zumer, Pascal Lamblin, Jean-Philippe Raymond, Guillaume Desjardins, Razvan Pascanu, David Warde-Farley, Atousa Torabi, Arjun Sharma, Emmanuel Bengio, Kishore Reddy Konda, Zhenzhou Wu:
Combining modality specific deep neural networks for emotion recognition in video. ICMI 2013: 543-550 - 2010
- [c1]Yevgeniya Sulema, Samira Ebrahimi Kahou:
Image compression: Comparative analysis of basic algorithms. EWDTS 2010: 534-537
Coauthor Index
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