Kahou, Samira Ebrahimi

37 publications

TMLR 2026 Towards Fair In-Context Learning with Tabular Foundation Models Patrik Kenfack, Samira Ebrahimi Kahou, Ulrich Aïvodji
TMLR 2025 Adaptive Group Robust Ensemble Knowledge Distillation Patrik Kenfack, Ulrich Aïvodji, Samira Ebrahimi Kahou
TMLR 2025 Behaviour Discovery and Attribution for Explainable Reinforcement Learning Rishav Rishav, Somjit Nath, Vincent Michalski, Samira Ebrahimi Kahou
ICLRW 2025 GradTune: Last-Layer Fine-Tuning for Group Robustness Without Group Annotation Patrik Kenfack, Ulrich Aïvodji, Samira Ebrahimi Kahou
ICLR 2025 Handling Delay in Real-Time Reinforcement Learning Ivan Anokhin, Rishav Rishav, Matthew Riemer, Stephen Chung, Irina Rish, Samira Ebrahimi Kahou
MLJ 2025 Source-Free Domain Adaptation Requires Penalized Diversity Laya Rafiee Sevyeri, Ivaxi Sheth, Farhood Farahnak, Alexandre See, Samira Ebrahimi Kahou, Thomas Fevens, Mohammad Havaei
ICLRW 2025 Towards Personalized Healthcare Without Harm via Bias Modulation Frank Ngaha, Patrik Kenfack, Ulrich Aïvodji, Samira Ebrahimi Kahou
TMLR 2024 A Survey on Fairness Without Demographics Patrik Joslin Kenfack, Samira Ebrahimi Kahou, Ulrich Aïvodji
TMLR 2024 Fairness Under Demographic Scarce Regime Patrik Joslin Kenfack, Samira Ebrahimi Kahou, Ulrich Aïvodji
ICMLW 2024 Handling Delay in Reinforcement Learning Caused by Parallel Computations of Neurons Ivan Anokhin, Rishav Rishav, Stephen Chung, Irina Rish, Samira Ebrahimi Kahou
ICML 2024 Learning to Play Atari in a World of Tokens Pranav Agarwal, Sheldon Andrews, Samira Ebrahimi Kahou
NeurIPS 2023 Auxiliary Losses for Learning Generalizable Concept-Based Models Ivaxi Sheth, Samira Ebrahimi Kahou
TMLR 2023 Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies Shivakanth Sujit, Pedro Braga, Jorg Bornschein, Samira Ebrahimi Kahou
ICML 2023 Discovering Object-Centric Generalized Value Functions from Pixels Somjit Nath, Gopeshh Subbaraj, Khimya Khetarpal, Samira Ebrahimi Kahou
NeurIPS 2023 Prioritizing Samples in Reinforcement Learning with Reducible Loss Shivakanth Sujit, Somjit Nath, Pedro Braga, Samira Ebrahimi Kahou
NeurIPSW 2022 Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies Shiva Kanth Sujit, Pedro Braga, Jorg Bornschein, Samira Ebrahimi Kahou
ICMLW 2022 Latent Variable Models for Bayesian Causal Discovery Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou
ICLR 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
NeurIPS 2022 Learning Robust Dynamics Through Variational Sparse Gating Arnav Kumar Jain, Shivakanth Sujit, Shruti Joshi, Vincent Michalski, Danijar Hafner, Samira Ebrahimi Kahou
NeurIPSW 2022 Learning from Uncertain Concepts via Test Time Interventions Ivaxi Sheth, Aamer Abdul Rahman, Laya Rafiee Sevyeri, Mohammad Havaei, Samira Ebrahimi Kahou
NeurIPSW 2022 Locally Constrained Representations in Reinforcement Learning Somjit Nath, Samira Ebrahimi Kahou
NeurIPSW 2022 Pitfalls of Conditional Computation for Multi-Modal Learning Ivaxi Sheth, Mohammad Havaei, Samira Ebrahimi Kahou
NeurIPSW 2022 Prioritizing Samples in Reinforcement Learning with Reducible Loss Shiva Kanth Sujit, Somjit Nath, Pedro Braga, Samira Ebrahimi Kahou
CVPR 2022 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
NeurIPSW 2021 Learning Robust Dynamics Through Variational Sparse Gating Arnav Kumar Jain, Shiva Kanth Sujit, Shruti Joshi, Vincent Michalski, Danijar Hafner, Samira Ebrahimi Kahou
NeurIPSW 2021 Shift and Scale Is Detrimental to Few-Shot Transfer Moslem Yazdanpanah, Aamer Abdul Rahman, Christian Desrosiers, Mohammad Havaei, Eugene Belilovsky, Samira Ebrahimi Kahou
CVPRW 2020 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
ICML 2019 Dead-Ends and Secure Exploration in Reinforcement Learning Mehdi Fatemi, Shikhar Sharma, Harm Van Seijen, Samira Ebrahimi Kahou
WACV 2019 Deep-Hurricane-Tracker: Tracking and Forecasting Extreme Climate Events Sookyung Kim, Hyojin Kim, Joonseok Lee, Sangwoong Yoon, Samira Ebrahimi Kahou, Karthik Kashinath, Prabhat
AAAI 2019 Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies Sarath Chandar, Chinnadhurai Sankar, Eugene Vorontsov, Samira Ebrahimi Kahou, Yoshua Bengio
NeurIPS 2018 Towards Deep Conversational Recommendations Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, Chris Pal
ICLR 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
NeurIPS 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, Mr. Prabhat, Chris Pal
CVPRW 2017 RATM: Recurrent Attentive Tracking Model Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic, Christopher Joseph Pal, Pascal Vincent
ICCV 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 Fruend, Peter Yianilos, Moritz Mueller-Freitag, Florian Hoppe, Christian Thurau, Ingo Bax, Roland Memisevic
ICLR 2015 FitNets: Hints for Thin Deep Nets Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, Yoshua Bengio
ECCVW 2014 Facial Expression Analysis Based on High Dimensional Binary Features Samira Ebrahimi Kahou, Pierre Froumenty, Christopher J. Pal