Image compression: Comparative analysis of basic algorithms. - Yevgeniya Sulema; Samira Ebrahimi Kahou (EWDTS, 2010)

Combining modality specific deep neural networks for emotion recognition in video. - 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; et al. (ICMI, 2013)

Facial Expression Analysis Based on High Dimensional Binary Features. - Samira Ebrahimi Kahou; Pierre Froumenty; Christopher J. Pal (ECCV Workshops (2), 2014)

Recurrent Neural Networks for Emotion Recognition in Video. - Samira Ebrahimi Kahou; Vincent Michalski; Kishore Reddy Konda; Roland Memisevic; Christopher Joseph Pal (ICMI, 2015)

RATM: Recurrent Attentive Tracking Model. - Samira Ebrahimi Kahou; Vincent Michalski; Roland Memisevic (CoRR, 2015)

FitNets: Hints for Thin Deep Nets. - Adriana Romero; Nicolas Ballas; Samira Ebrahimi Kahou; Antoine Chassang; Carlo Gatta; Yoshua Bengio (ICLR (Poster), 2015)

Theano: A Python framework for fast computation of mathematical expressions. - 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; et al. (CoRR, 2016)

Do Deep Convolutional Nets Really Need to be Deep (Or Even Convolutional)? - Gregor Urban; Krzysztof J. Geras; Samira Ebrahimi Kahou; Özlem Aslan; Shengjie Wang; Rich Caruana; Abdelrahman Mohamed; Matthai Philipose; Matthew Richardson (CoRR, 2016)

EmoNets: Multimodal deep learning approaches for emotion recognition in video. - 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; et al. (J. Multimodal User Interfaces, 2016)

RATM: Recurrent Attentive Tracking Model. - Samira Ebrahimi Kahou; Vincent Michalski; Roland Memisevic; Christopher Joseph Pal; Pascal Vincent (CVPR Workshops, 2017)

The "Something Something" Video Database for Learning and Evaluating Visual Common Sense. - 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; et al. (ICCV, 2017)

Do Deep Convolutional Nets Really Need to be Deep and Convolutional? - Gregor Urban; Krzysztof J. Geras; Samira Ebrahimi Kahou; Özlem Aslan; Shengjie Wang; Abdelrahman Mohamed; Matthai Philipose; Matthew Richardson; Rich Caruana (ICLR (Poster), 2017)

ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events. - Evan Racah; Christopher Beckham; Tegan Maharaj; Samira Ebrahimi Kahou; Prabhat; Chris Pal (NIPS, 2017)

FigureQA: An Annotated Figure Dataset for Visual Reasoning. - Samira Ebrahimi Kahou; Vincent Michalski; Adam Atkinson; Ákos Kádár; Adam Trischler; Yoshua Bengio (ICLR (Workshop), 2018)

ChatPainter: Improving Text to Image Generation using Dialogue. - Shikhar Sharma 001; Dendi Suhubdy; Vincent Michalski; Samira Ebrahimi Kahou; Yoshua Bengio (ICLR (Workshop), 2018)

Towards Deep Conversational Recommendations. - Raymond Li; Samira Ebrahimi Kahou; Hannes Schulz; Vincent Michalski; Laurent Charlin; Chris Pal (NeurIPS, 2018)

Keep Drawing It: Iterative language-based image generation and editing. - Alaaeldin El-Nouby; Shikhar Sharma 001; Hannes Schulz; R. Devon Hjelm; Layla El Asri; Samira Ebrahimi Kahou; Yoshua Bengio; Graham W. Taylor (CoRR, 2018)

Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies. - Sarath Chandar; Chinnadhurai Sankar; Eugene Vorontsov; Samira Ebrahimi Kahou; Yoshua Bengio (AAAI, 2019)

Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments. - Martin Weiss; Simon Chamorro; Roger Girgis; Margaux Luck; Samira Ebrahimi Kahou; Joseph Paul Cohen; Derek Nowrouzezahrai; Doina Precup; Florian Golemo; Chris Pal (CoRL, 2019)

Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction. - Alaaeldin El-Nouby; Shikhar Sharma 001; Hannes Schulz; R. Devon Hjelm; Layla El Asri; Samira Ebrahimi Kahou; Yoshua Bengio; Graham W. Taylor (ICCV, 2019)

Dead-ends and Secure Exploration in Reinforcement Learning. - Mehdi Fatemi; Shikhar Sharma 001; Harm van Seijen; Samira Ebrahimi Kahou (ICML, 2019)

Deep-Hurricane-Tracker: Tracking and Forecasting Extreme Climate Events. - Sookyung Kim; Hyojin Kim 001; Joonseok Lee; Sangwoong Yoon; Samira Ebrahimi Kahou; Karthik Kashinath; Prabhat (WACV, 2019)

An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation. - Vincent Michalski; Vikram Voleti; Samira Ebrahimi Kahou; Anthony Ortiz; Pascal Vincent; Chris Pal; Doina Precup (CoRR, 2019)

Multi-Image Super-Resolution for Remote Sensing using Deep Recurrent Networks. - Md Rifat Arefin; Vincent Michalski; Pierre-Luc St-Charles; Alfredo Kalaitzis; Sookyung Kim; Samira Ebrahimi Kahou; Yoshua Bengio (CVPR Workshops, 2020)

HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery. - Michel Deudon; Alfredo Kalaitzis; Israel Goytom; Md Rifat Arefin; Zhichao Lin; Kris Sankaran; Vincent Michalski; Samira Ebrahimi Kahou; Julien Cornebise; Yoshua Bengio (CoRR, 2020)

Predicting Regional Locust Swarm Distribution with Recurrent Neural Networks. - Hadia Mohmmed Osman Ahmed Samil; Annabelle Martin; Arnav Kumar Jain; Susan Amin; Samira Ebrahimi Kahou (CoRR, 2020)

Accounting for Variance in Machine Learning Benchmarks. - 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; et al. (MLSys, 2021)

Accounting for Variance in Machine Learning Benchmarks. - 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; et al. (CoRR, 2021)

Latent Variable Nested Set Transformers & AutoBots. - Roger Girgis; Florian Golemo; Felipe Codevilla; Jim Aldon D'Souza; Samira Ebrahimi Kahou; Felix Heide; Christopher J. Pal (CoRR, 2021)

Simple Video Generation using Neural ODEs. - David Kanaa; Vikram Voleti; Samira Ebrahimi Kahou; Christopher Pal (CoRR, 2021)

Revisiting Learnable Affines for Batch Norm in Few-Shot Transfer Learning. - Moslem Yazdanpanah; Aamer Abdul Rahman; Muawiz Chaudhary; Christian Desrosiers; Mohammad Havaei; Eugene Belilovsky; Samira Ebrahimi Kahou (CVPR, 2022)

Latent Variable Sequential Set Transformers for Joint Multi-Agent Motion Prediction. - Roger Girgis; Florian Golemo; Felipe Codevilla; Martin Weiss; Jim Aldon D'Souza; Samira Ebrahimi Kahou; Felix Heide; Christopher Pal (ICLR, 2022)

Learning Robust Dynamics through Variational Sparse Gating. - Arnav Kumar Jain; Shivakanth Sujit; Shruti Joshi; Vincent Michalski; Danijar Hafner; Samira Ebrahimi Kahou (NeurIPS, 2022)

FHIST: A Benchmark for Few-shot Classification of Histological Images. - Fereshteh Shakeri; Malik Boudiaf; Sina Mohammadi; Ivaxi Sheth; Mohammad Havaei; Ismail Ben Ayed; Samira Ebrahimi Kahou (CoRR, 2022)

Latent Variable Models for Bayesian Causal Discovery. - Jithendaraa Subramanian; Yashas Annadani; Ivaxi Sheth; Stefan Bauer; Derek Nowrouzezahrai; Samira Ebrahimi Kahou (CoRR, 2022)

Locally Constrained Representations in Reinforcement Learning. - Somjit Nath; Samira Ebrahimi Kahou (CoRR, 2022)

Learning Latent Structural Causal Models. - Jithendaraa Subramanian; Yashas Annadani; Ivaxi Sheth; Nan Rosemary Ke; Tristan Deleu; Stefan Bauer; Derek Nowrouzezahrai; Samira Ebrahimi Kahou (CoRR, 2022)

BERT on a Data Diet: Finding Important Examples by Gradient-Based Pruning. - Mohsen Fayyaz; Ehsan Aghazadeh; Ali Modarressi; Mohammad Taher Pilehvar; Yadollah Yaghoobzadeh; Samira Ebrahimi Kahou (CoRR, 2022)

Automatic Evaluation of Excavator Operators using Learned Reward Functions. - Pranav Agarwal; Marek Teichmann; Sheldon Andrews; Samira Ebrahimi Kahou (CoRR, 2022)

Pitfalls of Conditional Batch Normalization for Contextual Multi-Modal Learning. - Ivaxi Sheth; Aamer Abdul Rahman; Mohammad Havaei; Samira Ebrahimi Kahou (CoRR, 2022)

Discovering Object-Centric Generalized Value Functions From Pixels. - Somjit Nath; Gopeshh Raaj Subbaraj; Khimya Khetarpal; Samira Ebrahimi Kahou (ICML, 2023)

RelationalUNet for Image Segmentation. - Ivaxi Sheth; Pedro H. M. Braga; Shivakanth Sujit; Sahar Dastani; Samira Ebrahimi Kahou (MLMI@MICCAI (1), 2023)

Auxiliary Losses for Learning Generalizable Concept-based Models. - Ivaxi Sheth; Samira Ebrahimi Kahou (NeurIPS, 2023)

Prioritizing Samples in Reinforcement Learning with Reducible Loss. - Shivakanth Sujit; Somjit Nath; Pedro H. M. Braga; Samira Ebrahimi Kahou (NeurIPS, 2023)

Source-free Domain Adaptation Requires Penalized Diversity. - Laya Rafiee Sevyeri; Ivaxi Sheth; Farhood Farahnak; Alexandre See; Samira Ebrahimi Kahou; Thomas Fevens; Mohammad Havaei (CoRR, 2023)

CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning. - Nikunj Gupta; Samira Ebrahimi Kahou (CoRR, 2023)

Transformers in Reinforcement Learning: A Survey. - Pranav Agarwal; Aamer Abdul Rahman; Pierre-Luc St-Charles; Simon J. D. Prince; Samira Ebrahimi Kahou (CoRR, 2023)

Spectral Temporal Contrastive Learning. - Sacha Morin; Somjit Nath; Samira Ebrahimi Kahou; Guy Wolf (CoRR, 2023)

Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies. - Shivakanth Sujit; Pedro H. M. Braga; Jörg Bornschein; Samira Ebrahimi Kahou (Trans. Mach. Learn. Res., 2023)

From legacy to microservices: A type-based approach for microservices identification using machine learning and semantic analysis. - Imen Trabelsi 002; Manel Abdellatif; Abdalgader Abubaker; Naouel Moha; Sébastien Mosser 001; Samira Ebrahimi Kahou; Yann-Gaël Guéhéneuc (J. Softw. Evol. Process., 2023)

KD-LoRA: A Hybrid Approach to Efficient Fine-Tuning with LoRA and Knowledge Distillation. - Rambod Azimi; Rishav Rishav; Marek Teichmann; Samira Ebrahimi Kahou (ENLSP, 2024)

Learning to Play Atari in a World of Tokens. - Pranav Agarwal; Sheldon Andrews; Samira Ebrahimi Kahou (ICML, 2024)

On the Limits of Multi-modal Meta-Learning with Auxiliary Task Modulation Using Conditional Batch Normalization. - Jordi Armengol-Estapé; Vincent Michalski; Ramnath Kumar; Pierre-Luc St-Charles; Doina Precup; Samira Ebrahimi Kahou (CoRR, 2024)

Reinforcement Learning for Sequence Design Leveraging Protein Language Models. - Jithendaraa Subramanian; Shivakanth Sujit; Niloy Irtisam; Umong Sain; Derek Nowrouzezahrai; Samira Ebrahimi Kahou; Riashat Islam (CoRR, 2024)

Empowering Clinicians with Medical Decision Transformers: A Framework for Sepsis Treatment. - Aamer Abdul Rahman; Pranav Agarwal; Rita Noumeir; Philippe Jouvet; Vincent Michalski; Samira Ebrahimi Kahou (CoRR, 2024)

Learning Multi-agent Multi-machine Tending by Mobile Robots. - Abdalwhab Abdalwhab; Giovanni Beltrame; Samira Ebrahimi Kahou; David St-Onge (CoRR, 2024)

Prediction of Final Phosphorus Content of Steel in a Scrap-Based Electric Arc Furnace Using Artificial Neural Networks. - Riadh Azzaz; Valentin Hurel; Patrice Menard; Mohammad Jahazi; Samira Ebrahimi Kahou; Elmira Moosavi-Khoonsari (CoRR, 2024)

Adaptive Group Robust Ensemble Knowledge Distillation. - Patrik Joslin Kenfack; Ulrich Aïvodji; Samira Ebrahimi Kahou (CoRR, 2024)

Comparative Analysis of Diffusion Generative Models in Computational Pathology. - Denisha Thakkar; Vincent Quoc-Huy Trinh; Sonal Varma; Samira Ebrahimi Kahou; Hassan Rivaz; Mahdi S. Hosseini (CoRR, 2024)

A Survey on Fairness Without Demographics. - Patrik Joslin Kenfack; Samira Ebrahimi Kahou; Ulrich Aïvodji (Trans. Mach. Learn. Res., 2024)

Fairness Under Demographic Scarce Regime. - Patrik Joslin Kenfack; Samira Ebrahimi Kahou; Ulrich Aïvodji (Trans. Mach. Learn. Res., 2024)

Neural semantic tagging for natural language-based search in building information models: Implications for practice. - Mehrzad Shahinmoghadam; Samira Ebrahimi Kahou; Ali Motamedi 001 (Comput. Ind., 2024)

Handling Delay in Real-Time Reinforcement Learning. - Ivan Anokhin; Rishav Rishav; Matthew Riemer; Stephen Chung; Irina Rish; Samira Ebrahimi Kahou (ICLR, 2025)

Improving Quality Control of MRI Images Using Synthetic Motion Data. - Charles Bricout; Kang Ik Kevin Cho; Michael Harms; Ofer Pasternak; Carrie E. Bearden; Patrick D. McGorry; Rene S. Kahn; JM Kane; B. Nelson; Scott W. Woods; Martha Elizabeth Shenton; Sylvain Bouix; et al. (ISBI, 2025)

Improving Quality Control Of MRI Images Using Synthetic Motion Data. - Charles Bricout; Kang Ik Kevin Cho; Michael Harms; Ofer Pasternak; Carrie E. Bearden; Patrick D. McGorry; Rene S. Kahn; John Kane; Barnaby Nelson; Scott W. Woods; Martha Elizabeth Shenton; Sylvain Bouix; et al. (CoRR, 2025)

Behaviour Discovery and Attribution for Explainable Reinforcement Learning. - Rishav Rishav; Somjit Nath; Vincent Michalski; Samira Ebrahimi Kahou (CoRR, 2025)

Towards Fair In-Context Learning with Tabular Foundation Models. - Patrik Joslin Kenfack; Samira Ebrahimi Kahou; Ulrich Aïvodji (CoRR, 2025)

Estimating Head Motion in Structural MRI Using a Deep Neural Network Trained on Synthetic Artifacts. - Charles Bricout; Samira Ebrahimi Kahou; Sylvain Bouix (CoRR, 2025)

Cross-Layer Discrete Concept Discovery for Interpreting Language Models. - Ankur Garg; Xuemin Yu; Hassan Sajjad 001; Samira Ebrahimi Kahou (CoRR, 2025)

GitChameleon 2.0: Evaluating AI Code Generation Against Python Library Version Incompatibilities. - Diganta Misra; Nizar Islah; Victor May; Brice Rauby; Zihan Wang; Justine Gehring; Antonio Orvieto; Muawiz Chaudhary; Eilif B. Muller; Irina Rish; Samira Ebrahimi Kahou; Massimo Caccia (CoRR, 2025)

Zero-Shot Anomaly Detection with Dual-Branch Prompt Selection. - Zihan Wang; Samira Ebrahimi Kahou; Narges Armanfard (CoRR, 2025)