Please visit my Google Scholar profile for a complete list of my publications.

2024

  1. Neural Semantic Tagging for Natural Language-based Search in Building Information Models: Implications for Practice Shahinmoghadam, Mehrzad, Ebrahimi Kahou, Samira, and Motamedi, Ali Computers in Industry 2024, accepted

2023

  1. Transparent Anomaly Detection via Concept-based Explanations Sevyeri, Laya Rafiee, Sheth, Ivaxi, Farahnak, Farhood, Ebrahimi Kahou, Samira, and Enger, Shirin Abbasinejad In Advances in Neural Information Processing Systems workshop XAI in Action: Past, Present, and Future Applications 2023
  2. Empowering Clinicians with MeDT: A Framework for Sepsis Treatment Abdul Rahman, Aamer, Agarwal, Pranav, Michalski, Vincent, Noumeir, Rita, Jouvet, Philippe, and Ebrahimi Kahou, Samira In Advances in Neural Information Processing Systems workshop Goal-Conditioned Reinforcement Learning 2023, spotlight
  3. Spectral Temporal Contrastive Learning Morin, Sacha, Nath, Somjit, Ebrahimi Kahou, Samira, and Wolf, Guy In Advances in Neural Information Processing Systems workshop Self-Supervised Learning - Theory and Practice 2023
  4. Auxiliary Losses for Learning Generalizable Concept-based Models Sheth, Ivaxi, and Ebrahimi Kahou, Samira In Advances in Neural Information Processing Systems 2023
  5. Fairness Under Demographic Scarce Regime Kenfack, Patrik Joslin, Kahou, Samira Ebrahimi, and Aı̈vodji, Ulrich arXiv preprint arXiv:2307.13081 2023
  6. Relational UNet for Image Segmentation Sheth, Ivaxi, Braga, Pedro, Sujit, Shivakanth, Dastani Oghani, Sahar, and Ebrahimi Kahou, Samira International Conference on Medical Image Computing and Computer Assisted Intervention workshop Machine Learning in Medical Imaging 2023
  7. Transformers in Reinforcement Learning: A Survey Agarwal, Pranav, Rahman, Aamer Abdul, St-Charles, Pierre-Luc, Prince, Simon JD, and Kahou, Samira Ebrahimi arXiv preprint arXiv:2307.05979 2023
  8. CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning Gupta, Nikunj, and Kahou, Samira Ebrahimi Conference on Computer Vision and Pattern Recognition workshop Multi-Agent Behavior 2023
  9. Source-free Domain Adaptation Requires Penalized Diversity Sevyeri, Laya Rafiee, Sheth, Ivaxi, Farahnak, Farhood, See, Alexandre, Kahou, Samira Ebrahimi, Fevens, Thomas, and Havaei, Mohammad arXiv preprint arXiv:2304.02798 2023
  10. Overcoming Interpretability and Accuracy Trade-off in Medical Imaging Sheth, Ivaxi, and Kahou, Samira Ebrahimi In Medical Imaging with Deep Learning, short paper track 2023
  11. Discovering Object-Centric Generalized Value Functions From Pixels Nath, Somjit, Subbaraj, Gopeshh Raaj, Khetarpal, Khimya, and Kahou, Samira Ebrahimi In International Conference on Machine Learning 2023
  12. Bridging the Gap between Offline and Online Reinforcement Learning Evaluation Methodologies Sujit, Shivakanth, Braga, Pedro, Bornschein, Jörg, and Kahou, Samira Ebrahimi In Transactions on Machine Learning Research 2023 [Project Page]
  13. Prioritizing Samples in Reinforcement Learning with Reducible Loss Sujit, Shivakanth, Nath, Somjit, Braga, Pedro, and Kahou, Samira Ebrahimi In Advances in Neural Information Processing Systems 2023 [Project Page]

2022

  1. Automatic Evaluation of Excavator Operators using Learned Reward Functions Agarwal, Pranav, Teichmann, Marek, Andrews, Sheldon, and Kahou, Samira Ebrahimi In Advances in Neural Information Processing Systems workshop Reinforcement Learning for Real Life 2022 [Project Page]
  2. BERT on a Data Diet: Finding Important Examples by Gradient-Based Pruning Fayyaz, Mohsen, Aghazadeh, Ehsan, Modarressi, Seyed MohammadAli, Pilehvar, Mohammad Taher, Yaghoobzadeh, Yadollah, and Ebrahimi Kahou, Samira In Advances in Neural Information Processing Systems workshop Efficient Natural Language and Speech Processing (ENLSP-II): The Future of Pre-trained Models 2022
  3. Locally Constrained Representations in Reinforcement Learning Nath, Somjit, and Kahou, Samira Ebrahimi In Advances in Neural Information Processing Systems workshop Deep Reinforcement Learning 2022 [Code]
  4. Pitfalls of conditional batch normalisation for multi-modal learning Sheth, Ivaxi, Rahman, Aamer Abdul, Havaei, Mohammad, and Kahou, Samira Ebrahimi In Advances in Neural Information Processing Systems workshop I Can’t Believe It’s Not Better Workshop: Understanding Deep Learning Through Empirical Falsification 2022
  5. Learning from uncertain concepts via test time interventions Sheth, Ivaxi, Rahman, Aamer Abdul, Rafiee, Laya, Havaei, Mohammad, and Kahou, Samira Ebrahimi In Advances in Neural Information Processing Systems workshop Trustworthy and Socially Responsible Machine Learning 2022
  6. From legacy to microservices: A type-based approach for microservices identification using machine learning and semantic analysis Trabelsi, Imen, Abdellatif, Manel, Abubaker, Abdalgader, Moha, Naouel, Mosser, Sébastien, Ebrahimi-Kahou, Samira, and Guéhéneuc, Yann-Gaël Journal of Software: Evolution and Process 2022
  7. Latent Variable Models for Bayesian Causal Discovery Subramanian, Jithendaraa, Annadani, Yashas, Sheth, Ivaxi, Bauer, Stefan, Nowrouzezahrai, Derek, and Kahou, Samira Ebrahimi International Conference on Machine Learning workshop Spurious correlations, Invariance, and Stability (SCIS) 2022
  8. Detection of interictal epileptiform discharges on EEG and MEG Odonnat, Ambroise, Nasiotis, Konstantinos, Hill, Eleanor, Ebrahimi Kahou, Samira, Zheng, Jiayue, Enamundam, Naga Karthik, Baillet, Sylvain, Dudley, Roy W, and Cohen-Adad, Julien Abstract for the QBIN Conference 2022, best flash talk
  9. FHIST: A Benchmark for Few-shot Classification of Histological Images Shakeri, Fereshteh, Boudiaf, Malik, Mohammadi, Sina, Sheth, Ivaxi, Havaei, Mohammad, Ayed, Ismail Ben, and Kahou, Samira Ebrahimi arXiv preprint arXiv:2206.00092 2022
  10. Learning Robust Dynamics through Variational Sparse Gating Jain, Arnav Kumar, Sujit, Shiva Kanth, Joshi, Shruti, Michalski, Vincent, Hafner, Danijar, and Kahou, Samira Ebrahimi In Advances in Neural Information Processing Systems 2022 [Code]
  11. Revisiting BatchNorm’s Learnable Affines in Few-Shot Transfer Learning Yazdanpanah*, Moslem, Rahman*, Aamer Abdul, Desrosiers, Christian, Havaei, Mohammad, Belilovsky*, Eugene, and Kahou*, Samira Ebrahimi In Conference on Computer Vision and Pattern Recognition 2022
  12. Latent Variable Sequential Set Transformers for Joint Multi-Agent Motion Prediction Girgis, Roger, Golemo, Florian, Codevilla, Felipe, Weiss, Martin, D’Souza, Jim Aldon, Kahou, Samira Ebrahimi, Heide, Felix, and Pal, Christopher In International Conference on Learning Representations 2022, spotlight

2021

  1. Deep Learning for Detecting Extreme Weather Patterns Mudigonda, Mayur, Ram, Prabhat, Kashinath, Karthik, Racah, Evan, Mahesh, Ankur, Liu, Yunjie, Beckham, Christopher, Biard, Jim, Kurth, Thorsten, Kim, Sookyung, Kahou, Samira, and others, Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences 2021
  2. Accounting for variance in machine learning benchmarks Bouthillier, Xavier, Delaunay, Pierre, Bronzi, Mirko, Trofimov, Assya, Nichyporuk, Brennan, Szeto, Justin, Mohammadi Sepahvand, Nazanin, Raff, Edward, Madan, Kanika, Voleti, Vikram, Ebrahimi Kahou, Samira, Michalski, Vincent, Arbel, Tal, Pal, Chris, Varoquaux, Gael, and Vincent, Pascal Proceedings of Machine Learning and Systems 2021

2020

  1. Predicting Regional Locust Swarm Distribution with Recurrent Neural Networks Samil, Hadia Mohmmed Osman Ahmed, Martin, Annabelle, Jain, Arnav Kumar, Amin, Susan, and Kahou, Samira Ebrahimi Advances in Neural Information Processing Systems workshop AI for Humanitarian Assistance and Disaster Response 2020
  2. Multi-Image Super-Resolution for Remote Sensing Using Deep Recurrent Networks Arefin, Rifat, Michalski, Vincent, St-Charles, Pierre-Luc, Kalaitzis, Alfredo, Kim, Sookyung, Kahou, Samira E, and Bengio, Yoshua In Conference on Computer Vision and Pattern Recognition workshop EarthVision 2020

2019

  1. Simple Video Generation using Neural ODEs Kanaa*, David, Voleti*, Vikram, Kahou, Samira, and Pal, Christopher Advances in Neural Information Processing Systems workshop Learning with Rich Experience 2019
  2. HighRes-net: Multi-Frame Super-Resolution by Recursive Fusion Deudon*, Michel, Kalaitzis*, Alfredo, Goytom, Israel, Arefin, Rifat, Lin, Zhichao, Sankaran, Kris, Michalski, Vincent, Kahou, Samira E, Cornebise, Julien, and Bengio, Yoshua Advances in Neural Information Processing Systems workshop Science meets Engineering of Deep Learning 2019 [Code]
  3. Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments Weiss, Martin, Chamorro, Simon, Girgis, Roger, Luck, Margaux, Kahou, Samira E, Cohen, Joseph P, Nowrouzezahrai, Derek, Precup, Doina, Golemo, Florian, and Pal, Chris Conference on Robot Learning 2019 [Project Page]
  4. Tell, draw, and repeat: Generating and modifying images based on continual linguistic instruction El-Nouby, Alaaeldin, Sharma, Shikhar, Schulz, Hannes, Hjelm, Devon, Asri, Layla El, Kahou, Samira Ebrahimi, Bengio, Yoshua, and Taylor, Graham W In International Conference on Computer Vision 2019
  5. Dead-ends and Secure Exploration in Reinforcement Learning Fatemi, Mehdi, Sharma, Shikhar, Van Seijen, Harm, and Kahou, Samira Ebrahimi In International Conference on Machine Learning 2019
  6. An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation Michalski, Vincent, Voleti, Vikram, Kahou, Samira Ebrahimi, Ortiz, Anthony, Vincent, Pascal, Pal, Chris, and Precup, Doina International Conference on Machine Learning workshop Understanding and Improving Generalization in Deep Learning 2019
  7. Towards Non-saturating Recurrent Units for Modelling Long-term Dependencies Chandar*, Sarath, Sankar*, Chinnadhurai, Vorontsov, Eugene, Kahou, Samira Ebrahimi, and Bengio, Yoshua Association for the Advancement of Artificial Intelligence 2019
  8. Deep-hurricane-tracker: Tracking and forecasting extreme climate events Kim, Sookyung, Kim, Hyojin, Lee, Joonseok, Yoon, Sangwoong, Kahou, Samira Ebrahimi, Kashinath, Karthik, and Prabhat, Mr In Winter Conference on Applications of Computer Vision 2019, earlier version was presented at Climate Informatics 2018 (spotlight oral)

2018

  1. Towards deep conversational recommendations Li, Raymond, Kahou, Samira Ebrahimi, Schulz, Hannes, Michalski, Vincent, Charlin, Laurent, and Pal, Chris In Advances in Neural Information Processing Systems 2018 [Project Page]
  2. Chatpainter: Improving text to image generation using dialogue Sharma, Shikhar, Suhubdy, Dendi, Michalski, Vincent, Kahou, Samira Ebrahimi, and Bengio, Yoshua International Conference on Learning Representations workshop 2018
  3. ClimateNet: bringing the power of Deep Learning to the climate community via open datasets and architectures Prabhat, Mr, Kashinath, Karthik, Kurth, Thorsten, Mudigonda, Mayur, Mahesh, Ankur, Toms, Benjamin A, Biard, Jim, Kim, Soo Kyung, Kahou, Samira, Loring, Burlen, and others, In AGU Fall Meeting Abstracts 2018
  4. Tracking and Predicting Extreme Climate Events Kim, Soo Kyung, Yoon, Sangwoong, Lee, Joonseok, Kahou, Samira, Kim, Hyojin, Kashinath, Karthik, and Prabhat, Mr In AGU Fall Meeting Abstracts 2018
  5. Deep Learning recognizes weather and climate patterns Kashinath, Karthik, Prabhat, Mr, Mudigonda, Mayur, Mahesh, Ankur, Kim, Soo Kyung, Liu, Yunjie, Kahou, Samira, Toms, Benjamin A, Racah, Evan, Beckham, Christopher, and others, In AGU Fall Meeting Abstracts 2018
  6. Figureqa: An annotated figure dataset for visual reasoning Kahou*, Samira Ebrahimi, Michalski*, Vincent, Atkinson, Adam, Kádár, Ákos, Trischler, Adam, and Bengio, Yoshua International Conference on Learning Representations workshop 2018, also oral presentation at Montréal AI Symposium 2017 [Code] [Project Page]

2017

  1. Extremeweather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events Racah, Evan, Beckham, Christopher, Maharaj, Tegan, Kahou, Samira Ebrahimi, Prabhat, Mr, and Pal, Chris In Advances in Neural Information Processing Systems 2017 [Project Page]
  2. Segmenting and tracking extreme climate events using neural networks Kim, Sookyung, Mudigonda, Mayur, Mahesh, Ankur, Kahou, Samira, Kashinath, Karthik, Williams, Dean, Michalski, Vincent, O’Brien, Travis, and Prabhat, Mr Advances in Neural Information Processing Systems workshop Deep Learning for Physical Science 2017
  3. The "Something Something" Video Database for Learning and Evaluating Visual Common Sense Goyal, Raghav, Kahou, Samira Ebrahimi, Michalski, Vincent, Materzynska, Joanna, Westphal, Susanne, Kim, Heuna, Haenel, Valentin, Fruend, Ingo, Yianilos, Peter, Mueller-Freitag, Moritz, and others, In International Conference on Computer Vision 2017 [Project Page]
  4. RATM: Recurrent attentive tracking model Ebrahimi Kahou, Samira, Michalski, Vincent, Memisevic, Roland, Pal, Christopher, and Vincent, Pascal In Conference on Computer Vision and Pattern Recognition workshop Brave New Ideas in Motion Representations 2017, oral presentation [Code]
  5. ClimateNet: a machine learning dataset for climate science research Prabhat, Mr, Biard, Jim, Ganguly, Sangram, Ames, Sasha, Kashinath, Karthik, Kim, Soo Kyung, Kahou, Samira, Maharaj, Tegan, Beckham, Christopher, O’Brien, Travis Allen, and others, In AGU fall meeting abstracts 2017
  6. Assessing uncertainty in deep learning techniques that identify atmospheric rivers in climate simulations Mahesh, Ankur, Mudigonda, Mayur, Kim, Soo Kyung, Kashinath, Karthik, Kahou, Samira, Michalski, Vincent, Williams, Dean Norman, Liu, Yunjie, Prabhat, Mr, Loring, Burlen, and others, In AGU Fall Meeting Abstracts 2017
  7. Deep learning for extreme weather detection Prabhat, Mr, Racah, Evan, Biard, Jim, Liu, Yunjie, Mudigonda, Mayur, Kashinath, Karthik, Beckham, Christopher, Maharaj, Tegan, Kahou, Samira, Pal, Chris, and others, In AGU Fall Meeting Abstracts 2017
  8. Do deep convolutional nets really need to be deep and convolutional? Urban, Gregor, Geras, Krzysztof J, Kahou, Samira Ebrahimi, Aslan, Ozlem, Wang, Shengjie, Caruana, Rich, Mohamed, Abdelrahman, Philipose, Matthai, and Richardson, Matt International Conference on Learning Representations 2017

2016

  1. Emotion Recognition with Deep Neural Networks Ebrahimi Kahou, Samira 2016, Best Thesis Award in the Department of Computer Engineering [PDF] [Slides]
  2. Theano: A Python framework for fast computation of mathematical expressions The Theano Development Team, Technical Report 2016 [arXiv]
  3. Emonets: Multimodal deep learning approaches for emotion recognition in video Kahou, Samira Ebrahimi, Bouthillier, Xavier, Lamblin, Pascal, Gulcehre, Caglar, Michalski, Vincent, Konda, Kishore, Jean, Sébastien, Froumenty, Pierre, Dauphin, Yann, Boulanger-Lewandowski, Nicolas, and others, Journal on Multimodal User Interfaces 2016 [arXiv]

2015

  1. Recurrent neural networks for emotion recognition in video Ebrahimi Kahou, Samira, Michalski, Vincent, Konda, Kishore, Memisevic, Roland, and Pal, Christopher In International Conference on Multimodal Interaction 2015, Entry to the ICMI 2015 Grand Challenge on Emotion Recognition in the Wild (2nd runner up) [PDF] [Code]
  2. Fitnets: Hints for thin deep nets Romero, Adriana, Ballas, Nicolas, Kahou, Samira Ebrahimi, Chassang, Antoine, Gatta, Carlo, and Bengio, Yoshua International Conference on Learning Representations 2015

2014

  1. Facial expression analysis based on high dimensional binary features Kahou, Samira Ebrahimi, Froumenty, Pierre, and Pal, Christopher In European Conference on Computer Vision workshop on computer vision with local binary patterns 2014, Best Paper Award [PDF]

2013

  1. Combining modality specific deep neural networks for emotion recognition in video Kahou, Samira Ebrahimi, Pal, Christopher, Bouthillier, Xavier, Froumenty, Pierre, Gülçehre, Çaglar, Memisevic, Roland, Vincent, Pascal, Courville, Aaron, Bengio, Yoshua, Ferrari, Raul Chandias, and others, In International Conference on Multimodal Interaction 2013, Winning entry to the ICMI 2013 Grand Challenge on Emotion Recognition in the Wild, Ten-Year Technical Impact Runner-Up at ICMI 2023 [PDF]