Publications

Every public publication from the academic CV, with archived PDFs where available. Titles and venues are shown in their original language. 85 publications.

Selected publications

  • 2020A trend ribbon and a seasonal ribbon combining into one forecast curve
    N-BEATS: Neural basis expansion analysis for interpretable time series forecasting
    Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio · International Conference on Learning Representations

    Interpretable deep forecasting; the most cited of these works.

  • 2024Conceptual illustration of open code models built from a large public code corpus
    StarCoder 2 and The Stack v2: The Next Generation
    Anton Lozhkov, Raymond Li, Loubna Ben Allal, Federico Cassano, Joel Lamy-Poirier, Nouamane Tazi, Ao Tang, Dmytro Pykhtar, Jiawei Liu, Yuxiang Wei, Tianyang Liu, Max Tian, Denis Kocetkov, Arthur Zucker, Younes Belkada, Zijian Wang, Qian Liu, Dmitry Abulkhanov, Indraneil Paul, Zhuang Li, Wen-Ding Li, Megan Risdal, Jia Li, Jian Zhu, Terry Yue Zhuo, Evgenii Zheltonozhskii, Nii Osae Osae Dade, Wenhao Yu, Lucas Krauß, Naman Jain, Yixuan Su, Xuanli He, Manan Dey, Edoardo Abati, Yekun Chai, Niklas Muennighoff, Xiangru Tang, Muhtasham Oblokulov, Christopher Akiki, Marc Marone, Chenghao Mou, Mayank Mishra, Alex Gu, Binyuan Hui, Tri Dao, Armel Zebaze, Olivier Dehaene, Nicolas Patry, Canwen Xu, Julian McAuley, Han Hu, Torsten Scholak, Sebastien Paquet, Jennifer Robinson, Carolyn Jane Anderson, Nicolas Chapados, Mostofa Patwary, Nima Tajbakhsh, Yacine Jernite, Carlos Muñoz Ferrandis, Lingming Zhang, Sean Hughes, Thomas Wolf, Arjun Guha, Leandro von Werra, Harm de Vries · BigCode Project Technical Report

    Open code models and their training data, with the BigCode community.

  • 2024Conceptual illustration of a language model turned into a text encoder
    LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
    Parishad BehnamGhader, Vaibhav Adlakha, Marius Mosbach, Dzmitry Bahdanau, Nicolas Chapados, Siva Reddy · First Conference on Language Modeling (COLM 2024)

    Turning decoder-only language models into strong text encoders.

  • 2024Conceptual illustration of a web agent working through enterprise software tasks
    WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
    Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, David Vázquez, Nicolas Chapados, Alexandre Lacoste · Proceedings of the 41st International Conference on Machine Learning (ICML 2024)

    Benchmarking web agents on real knowledge-work tasks.

  • 2023
    Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
    Kashif Rasul, Arjun Ashok, Andrew Robert Williams, Hena Ghonia, Rishika Bhagwatkar, Arian Khorasani, Mohammad Javad Darvishi Bayazi, George Adamopoulos, Roland Riachi, Nadhir Hassen, Marin Biloš, Sahil Garg, Anderson Schneider, Nicolas Chapados, Alexandre Drouin, Valentina Zantedeschi, Yuriy Nevmyvaka, Irina Rish · NeurIPS 2023 Workshop on Robustness of Few-shot and Zero-shot Learning in Large Foundation Models (R0-FoMo)

    A foundation model for probabilistic time-series forecasting.

  • 2016
    HeMIS: Hetero-Modal Image Segmentation
    Mohammad Havaei, Nicolas Guizard, Nicolas Chapados, Yoshua Bengio · Medical Image Computing and Computer-Assisted Intervention (MICCAI 2016). Lecture Notes in Computer Science, vol. 9901

    Segmenting medical images when some modalities are missing.

  • 2022
    TACTiS: Transformer-Attentional Copulas for Time Series
    Alexandre Drouin, Étienne Marcotte, Nicolas Chapados · Proceedings of the 39th International Conference on Machine Learning

    Copulas meet transformers for multivariate forecasting.

  • 2025Conceptual illustration of a forecast informed by textual context
    Context is Key: A Benchmark for Forecasting with Essential Textual Information
    Andrew Robert Williams, Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin · Proceedings of the 42nd International Conference on Machine Learning (ICML 2025)

    Forecasting with the textual context practitioners actually have.

Books and book chapters

  • 2023
    Explaining Explainable AI
    Richard Zuroff, Nicolas Chapados · Artificial Intelligence in Finance: Challenges, Opportunities and Regulatory Developments
  • 2018
    Information Fusion in Deep Convolutional Neural Networks for Biomedical Image Segmentation
    Mohammad Havaei, Nicolas Guizard, Nicolas Chapados, Yoshua Bengio · Signal Processing and Machine Learning for Biomedical Big Data
  • 2011
    Portfolio Choice Problems: an Introductory Survey of Single and Multiperiod Models
    Nicolas Chapados · Springer
  • 2010
    Algorithmes d'apprentissage en gestion de portefeuille: optimisation et combinaison de réseaux de neurones; application à la répartition d'actifs sous contrainte de valeur à risque
    Nicolas Chapados · Éditions Universitaires Européennes
  • 2003
    Statistical Learning Algorithms Applied to Automobile Insurance Ratemaking
    Charles Dugas, Yoshua Bengio, Nicolas Chapados, Pascal Vincent, Germain Denoncourt, Christian Fournier · Intelligent Techniques for The Insurance Industry: Theory and Applications

Refereed journal articles

  • 2026
    Beyond Naïve Prompting: Strategies for Improved Context-aided Forecasting with LLMs
    Arjun Ashok, Andrew Robert Williams, Vincent Zhihao Zheng, Irina Rish, Nicolas Chapados, Étienne Marcotte, Valentina Zantedeschi, Alexandre Drouin · Transactions on Machine Learning Research
  • 2025
    Spaced Scheduling for Large Language Model Training
    Amine El Hattami, Nicolas Chapados, Christopher Pal · Transactions on Machine Learning Research
  • 2025Conceptual illustration of a shared environment for evaluating web agents
    The BrowserGym Ecosystem for Web Agent Research
    Thibault Le Sellier de Chezelles, Maxime Gasse, Alexandre Drouin, Massimo Caccia, Léo Boisvert, Megh Thakkar, Tom Marty, Rim Assouel, Sahar Omidi Shayegan, Lawrence Keunho Jang, Xing Han Lù, Ori Yoran, Dehan Kong, Frank F. Xu, Siva Reddy, Quentin Cappart, Graham Neubig, Ruslan Salakhutdinov, Nicolas Chapados, Alexandre Lacoste · Transactions on Machine Learning Research
  • 2024
    Dynamic Routing and Wavelength Assignment with Reinforcement Learning
    Peyman Kafaei, Quentin Cappart, Nicolas Chapados, Hamed Pouya, Louis-Martin Rousseau · INFORMS Journal on Optimization
  • 2021
    Graph neural networks and deep reinforcement learning for simultaneous beam orientation and trajectory optimization of Cyberknife
    Peyman Kafaei, Quentin Cappart, Marc-Andre Renaud, Nicolas Chapados, Louis-Martin Rousseau · Physics in Medicine & Biology
  • 2019
    Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model
    Michael F Byrne, Nicolas Chapados, Florian Soudan, Clemens Oertel, Milagros Linares Perez, Raymond Kelly, Nadeem Iqbal, Florent Chandelier, Douglas K Rex · Gut
  • 2014
    Retail store scheduling for profit
    Nicolas Chapados, Marc Joliveau, Pierre L’Ecuyer, Louis-Martin Rousseau · European Journal of Operational Research
  • 2012
    Detonation Classification from Acoustic Signature with the Restricted Boltzmann Machine
    Yoshua Bengio, Nicolas Chapados, Olivier Delalleau, Christian Hudon, Xavier Saint-Mleux, Hugo Larochelle, Jérôme Louradour · Computational Intelligence
  • 2011
    A High-Order Feature Synthesis and Selection Algorithm Applied to Insurance Risk Modelling
    Charles Dugas, Nicolas Chapados, Réjean Ducharme, Xavier Saint-Mleux, Pascal Vincent · International Journal of Business Intelligence and Data Mining
  • 2007
    Noisy K Best-Paths for Approximate Dynamic Programming with Application to Portfolio Optimization
    Nicolas Chapados, Yoshua Bengio · Journal of Computers
  • 2003
    Extensions to Metric-Based Model Selection
    Yoshua Bengio, Nicolas Chapados · Journal of Machine Learning Research
  • 2001
    Cost Functions and Model Combination for VaR-Based Asset Allocation Using Neural Networks
    Nicolas Chapados, Yoshua Bengio · IEEE Transactions on Neural Networks

Refereed conference proceedings

  • 2026
    DRBench: A Realistic Benchmark for Enterprise Deep Research
    Amirhossein Abaskohi, Tianyi Chen, Miguel Muñoz-Mármol, Curtis Fox, Amrutha Varshini Ramesh, Étienne Marcotte, Xing Han Lù, Nicolas Chapados, Spandana Gella, Christopher Pal, Alexandre Drouin, Issam H. Laradji · International Conference on Learning Representations (ICLR 2026)
  • 2026
    Grounding Computer Use Agents on Human Demonstrations
    Aarash Feizi, Shravan Nayak, Xiangru Jian, Kevin Qinghong Lin, Kaixin Li, Rabiul Awal, Xing Han Lù, Johan S. Obando-Ceron, Juan A. Rodríguez, Nicolas Chapados, David Vázquez, Adriana Romero-Soriano, Reihaneh Rabbany, Perouz Taslakian, Christopher Pal, Spandana Gella, Sai Rajeswar · International Conference on Learning Representations (ICLR 2026)
  • 2026
    LLM2Vec-Gen: Generative Embeddings from Large Language Models
    Parishad BehnamGhader, Vaibhav Adlakha, Fabian David Schmidt, Nicolas Chapados, Marius Mosbach, Siva Reddy · Conference on Language Modeling (COLM 2026)
  • 2026
    Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain
    Léo Boisvert, Abhay Puri, Chandra Kiran Reddy Evuru, Nazanin Mohammadi Sepahvand, Nicolas Chapados, Quentin Cappart, Alexandre Lacoste, Krishnamurthy Dvijotham, Alexandre Drouin, Jason Stanley · Proceedings of the ACM Conference on AI and Agentic Systems (CAIS 2026)
  • 2026
    Societal Frameworks Can Improve LLM Alignment
    Karolina Stańczak, Nicholas Meade, Mehar Bhatia, Hattie Zhou, Konstantin Böttinger, Jeremy Barnes, Jason Stanley, Nicolas Papernot, Nicolas Chapados, Denis Therien, Timothy P. Lillicrap, Ana Marasović, Sylvie Delacroix, Gillian K. Hadfield, Siva Reddy · Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency (FAccT 2026)
  • 2025
    AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Document Understanding
    Ahmed Masry, Juan A. Rodríguez, Tianyu Zhang, Suyuchen Wang, Chao Wang, Aarash Feizi, Akshay Kalkunte Suresh, Abhay Puri, Xiangru Jian, Pierre-André Noël, Sathwik Tejaswi Madhusudhan, Marco Pedersoli, Bang Liu, Nicolas Chapados, Yoshua Bengio, Enamul Hoque, Christopher Pal, Issam Hadj Laradji, David Vázquez, Perouz Taslakian, Spandana Gella, Sai Rajeswar · Advances in Neural Information Processing Systems 38 (NeurIPS 2025)
  • 2025
    BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks
    Juan A. Rodríguez, Xiangru Jian, Siba Smarak Panigrahi, Tianyu Zhang, Aarash Feizi, Abhay Puri, Akshay Kalkunte, François Savard, Ahmed Masry, Shravan Nayak, Rabiul Awal, Mahsa Massoud, Amirhossein Abaskohi, Zichao Li, Suyuchen Wang, Pierre-André Noël, Mats Leon Richter, Saverio Vadacchino, Shubbam Agarwal, Sanket Biswas, Sara Shanian, Ying Zhang, Noah Bolger, Kurt MacDonald, Simon Fauvel, Sathwik Tejaswi, Srinivas Sunkara, João Monteiro, Krishnamurthy Dj Dvijotham, Torsten Scholak, Nicolas Chapados, Sepideh Kharagani, Sean Hughes, M. Tamer Özsu, Siva Reddy, Marco Pedersoli, Yoshua Bengio, Christopher Pal, Issam H. Laradji, Spandana Gella, Perouz Taslakian, David Vázquez, Sai Rajeswar · International Conference on Learning Representations (ICLR 2025)
  • 2025Conceptual illustration of a forecast informed by textual context
    Context is Key: A Benchmark for Forecasting with Essential Textual Information
    Andrew Robert Williams, Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin · Proceedings of the 42nd International Conference on Machine Learning (ICML 2025)
  • 2025
    InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation
    Gaurav Sahu, Abhay Puri, Juan A. Rodríguez, Amirhossein Abaskohi, Mohammad Chegini, Alexandre Drouin, Perouz Taslakian, Valentina Zantedeschi, Alexandre Lacoste, David Vázquez, Nicolas Chapados, Christopher Pal, Sai Rajeswar, Issam H. Laradji · International Conference on Learning Representations (ICLR 2025)
  • 2025
    UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interaction
    Shravan Nayak, Xiangru Jian, Kevin Qinghong Lin, Juan A. Rodríguez, Montek Kalsi, Nicolas Chapados, M. Tamer Özsu, Aishwarya Agrawal, David Vázquez, Christopher Pal, Perouz Taslakian, Spandana Gella, Sai Rajeswar · Proceedings of the 42nd International Conference on Machine Learning (ICML 2025)
  • 2024Conceptual illustration of a language model turned into a text encoder
    LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
    Parishad BehnamGhader, Vaibhav Adlakha, Marius Mosbach, Dzmitry Bahdanau, Nicolas Chapados, Siva Reddy · First Conference on Language Modeling (COLM 2024)
  • 2024
    RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Content
    João Monteiro, Pierre-André Noël, Étienne Marcotte, Sai Rajeswar, Valentina Zantedeschi, David Vázquez, Nicolas Chapados, Christopher Pal, Perouz Taslakian · Advances in Neural Information Processing Systems 37 (NeurIPS 2024), Datasets and Benchmarks Track
  • 2024
    TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series
    Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Nicolas Chapados, Alexandre Drouin · International Conference on Learning Representations (ICLR 2024)
  • 2024Conceptual illustration of a web agent working through enterprise software tasks
    WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
    Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, David Vázquez, Nicolas Chapados, Alexandre Lacoste · Proceedings of the 41st International Conference on Machine Learning (ICML 2024)
  • 2024Conceptual illustration of compositional, multi-step knowledge-work tasks
    WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks
    Léo Boisvert, Megh Thakkar, Maxime Gasse, Massimo Caccia, Thibault Le Sellier de Chezelles, Quentin Cappart, Nicolas Chapados, Alexandre Lacoste, Alexandre Drouin · Advances in Neural Information Processing Systems 37 (NeurIPS 2024), Datasets and Benchmarks Track
  • 2024
    XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference
    João Monteiro, Étienne Marcotte, Pierre-André Noël, Valentina Zantedeschi, David Vázquez, Nicolas Chapados, Christopher Pal, Perouz Taslakian · Findings of the Association for Computational Linguistics: EMNLP 2024
  • 2023
    Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts
    Étienne Marcotte, Valentina Zantedeschi, Alexandre Drouin, Nicolas Chapados · Proceedings of the 40th International Conference on Machine Learning (ICML 2023)
  • 2022
    TACTiS: Transformer-Attentional Copulas for Time Series
    Alexandre Drouin, Étienne Marcotte, Nicolas Chapados · Proceedings of the 39th International Conference on Machine Learning
  • 2021
    Meta-learning framework with applications to zero-shot time-series forecasting
    Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio · Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence
  • 2020A trend ribbon and a seasonal ribbon combining into one forecast curve
    N-BEATS: Neural basis expansion analysis for interpretable time series forecasting
    Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio · International Conference on Learning Representations
  • 2019
    Learning to Learn with Conditional Class Dependencies
    Xiang Jiang, Mohammad Havaei, Farshid Varno, Gabriel Chartrand, Nicolas Chapados, Stan Matwin · International Conference on Learning Representations
  • 2018
    Real-Time Artificial Intelligence “Full Colonoscopy Workflow” for Automatic Detection Followed by Optical Biopsy of Colorectal Polyps
    Michael F. Byrne, Florian Soudan, Milagros Henkel, Clemens Oertel, Nicolas Chapados, Francisco J. Echagüe, Sina Hamidi Ghalehjegh, Nicolas Guizard, Sébastien Giguère, Margaret E. MacPhail, Andrew Sullivan, Florent Chandelier, Douglas K. Rex · Gastrointestinal Endoscopy
  • 2017
    Artificial Intelligence (AI) in Endoscopy–-Deep Learning for Optical Biopsy of Colorectal Polyps in Real-Time on Unaltered Endoscopic Videos
    Michael F. Byrne, Nicolas Chapados, Florian Soudan, Clemens Oertel, Milagros L. Linares Pérez, Raymond Kelly, Nadeem Iqbal, Florent Chandelier, Douglas K. Rex · Gastrointestinal Endoscopy
  • 2017
    CASED: Curriculum Adaptive Sampling for Extreme Data Imbalance
    Andrew Jesson, Nicolas Guizard, Sina Hamidi Ghalehjegh, Damien Goblot, Florian Soudan, Nicolas Chapados · Medical Image Computing and Computer-Assisted Intervention (MICCAI 2017). Lecture Notes in Computer Science, vol. 10435
  • 2016
    Artificial Intelligence (Ai) In Endoscopy–Deep Learning For Optical Biopsy Of Colorectal Polyps In Real-Time On Unaltered Endoscopic Videos
    Michael F. Byrne, Douglas K. Rex, Nicolas Chapados, Florian Soudan, Clemens Oertel, Milagros Linares Perez, R. Kelly, N. Iqbal, Florent Chandelier · United European Gastroenterology Journal
  • 2016
    Automated Segmentation of Liver Metastases with Deep Convolutional Neural Networks
    Eugene Vorontsov, Gabriel Chartrand, Olina Dagher, Vi Thuy Tran, Mathieu Flamand, Aline Khatchikian, Amine Smouk, Nicolas Siron, Anne-Catherine Maynard-Paquette, David Roy, Nicolas Chapados, Simon Turcotte, Real Lapointe, Franck Vandenbroucke-Menu, Bich Nguyen, Christopher Pal, Samuel Kadoury, An Tang · Radiological Society of North America 2016 Scientific Assembly and Annual Meeting
  • 2016
    HeMIS: Hetero-Modal Image Segmentation
    Mohammad Havaei, Nicolas Guizard, Nicolas Chapados, Yoshua Bengio · Medical Image Computing and Computer-Assisted Intervention (MICCAI 2016). Lecture Notes in Computer Science, vol. 9901
  • 2014
    Effective Bayesian Modeling of Groups of Related Count Time Series
    Nicolas Chapados · Journal of Machine Learning Research, Workshop and Conference Proceedings
  • 2011
    Retail Store Workforce Scheduling by Expected Operating Income Maximization
    Nicolas Chapados, Marc Joliveau, Louis-Martin Rousseau · Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
  • 2009
    Statistical Machine Learning Algorithms for Target Classification from Acoustic Signature
    Vincent Mirelli, Stephen Tenney, Yoshua Bengio, Nicolas Chapados, Olivier Delalleau · Military Sensors and Systems
  • 2008
    Augmented Functional Time Series Representation and Forecasting with Gaussian Processes
    Nicolas Chapados, Yoshua Bengio · Advances in Neural Information Processing Systems 20
  • 2008
    Scoring Models for Insurance Risk Sharing Pool Optimization
    Nicolas Chapados, Charles Dugas, Pascal Vincent, Réjean Ducharme · Second International Workshop on Domain Driven Data Mining
  • 2006
    The K Best-Paths Approach to Approximate Dynamic Programming with Application to Portfolio Optimization
    Nicolas Chapados, Yoshua Bengio · Advances in Artificial Intelligence, Proceedings of the 19th Conference of the Canadian Society for Computational Studies of Intelligence
  • 2002
    Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference
    Nicolas Chapados, Yoshua Bengio, Pascal Vincent, Charles Dugas Joumana Ghosn, Ichiro Takeuchi, Linyan Meng · Advances in Neural Information Processing Systems 14
  • 2002
    Metric-Based Model Selection for Time-Series Forecasting
    Yoshua Bengio, Nicolas Chapados · Neural Networks for Signal Processing XII
  • 2001
    Input Decay: Simple and Effective Soft Variable Selection
    Nicolas Chapados, Yoshua Bengio · Proceedings of the IEEE/INNS International Joint Conference on Neural Networks 2001
  • 2000
    Cost Functions and Model Combination for VaR-Based Asset Allocation Using Neural Networks
    Nicolas Chapados, Yoshua Bengio · Computational Finance 2000
  • 1999
    A Mixed-Initiative Natural Dialogue System for Conference Room Reservation
    Claudia Pateras, Nicolas Chapados, Remi Kwan, Dominic Lavoie, Réal Tremblay · Proceedings of the EuroSpeech'99 Conference

Workshop presentations

  • 2026
    SKILL.nb: Selective Formalization and Gated Execution for Durable Agent Workflows
    Amine El Hattami, Nicolas Chapados, Christopher Pal · ICML 2026 Workshop on Failure Modes in Agentic AI (FAGEN)
  • 2025
    Silent Sabotage: Injecting Backdoors into AI Agents Through Fine-Tuning
    Léo Boisvert, Abhay Puri, Chandra Kiran Reddy Evuru, Joshua Kazdan, Avinandan Bose, Quentin Cappart, Maryam Fazel, Sai Rajeswar, Jason Stanley, Nicolas Chapados, Alexandre Drouin, Krishnamurthy Dj Dvijotham · ICML 2025 Workshop on Computer Use Agents
  • 2025
    WebArena Verified: Reliable Evaluation for Web Agents
    Amine El Hattami, Megh Thakkar, Nicolas Chapados, Christopher Pal · NeurIPS 2025 Workshop on Scaling Environments for Agents (SEA)
  • 2024
    Fine-Tuning Web Agents: It Works, But It's Trickier Than You Think
    Massimo Caccia, Megh Thakkar, Léo Boisvert, Thibault Le Sellier de Chezelles, Alexandre Piché, Nicolas Chapados, Alexandre Drouin, Maxime Gasse, Alexandre Lacoste · NeurIPS 2024 Workshop on Open-World Agents
  • 2023
    Capture the Flag: Uncovering Data Insights with Large Language Models
    Issam Laradji, Perouz Taslakian, Sai Rajeswar, Valentina Zantedeschi, Alexandre Lacoste, Nicolas Chapados, David Vázquez, Christopher Pal, Alexandre Drouin · NeurIPS 2023 Workshop on Foundation Models for Decision Making
  • 2023
    Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
    Kashif Rasul, Arjun Ashok, Andrew Robert Williams, Hena Ghonia, Rishika Bhagwatkar, Arian Khorasani, Mohammad Javad Darvishi Bayazi, George Adamopoulos, Roland Riachi, Nadhir Hassen, Marin Biloš, Sahil Garg, Anderson Schneider, Nicolas Chapados, Alexandre Drouin, Valentina Zantedeschi, Yuriy Nevmyvaka, Irina Rish · NeurIPS 2023 Workshop on Robustness of Few-shot and Zero-shot Learning in Large Foundation Models (R0-FoMo)
  • 2023
    The Unsolved Challenges of LLMs as Generalist Web Agents: A Case Study
    Rim Assouel, Tom Marty, Massimo Caccia, Issam Laradji, Alexandre Drouin, Sai Rajeswar, Hector Palacios, Quentin Cappart, David Vázquez, Nicolas Chapados, Maxime Gasse, Alexandre Lacoste · NeurIPS 2023 Workshop on Foundation Models for Decision Making
  • 2018
    Adversarially Learned Mixture Model
    Andrew Jesson, Cécile Low-Kam, Florian Soudan, Nicolas Chapados · Theoretical Foundations and Applications of Deep Generative Models, ICML 2018
  • 2018
    Attentive Task-Agnostic Meta-Learning for Few-Shot Text Classification
    Xiang Jiang, Mohammad Havaei, Gabriel Chartrand, Hassan Chouaib, Thomas Vincent, Andrew Jesson, Nicolas Chapados · NeurIPS 2018 Second Workshop on Meta-Learning
  • 2017
    Data imputation with latent variable models
    Michal Drozdzal, Mohammad Havaei, Chin-Way Huang, Laurent Charlin, Nicolas Chapados, Aaron Courville · Montreal AI Symposium 2017
  • 2014
    Hierarchical Bayesian State-Space Model for Call Center Arrival Rate Forecasting
    Nicolas Chapados, Pierre L’Ecuyer · Journées de l'optimisation 2014
  • 2011
    Stochastic Modeling of Retail Stores for Workforce Management
    Nicolas Chapados, Marc Joliveau, Louis-Martin Rousseau · 2011 INFORMS Simulation Society Research Workshop
  • 2010
    Non-Parametric Volatility Forecasting with Gaussian Processes
    Nicolas Chapados, Christian Dorion · 16th International Conference on Computing in Economics and Finance
  • 2007
    Forecasting Commodity Contract Spreads with Gaussian Processes
    Nicolas Chapados, Yoshua Bengio · 13th International Conference on Computing in Economics and Finance
  • 2006
    The PLearn Machine Learning Library
    Pascal Vincent, Nicolas Chapados · NIPS Workshop on Machine Learning Open Source Software
  • 2005
    The K-Shortest-Paths Approach to Approximate Dynamic Programming
    Nicolas Chapados, Yoshua Bengio · NIPS 2005 Workshop on Machine Learning in Finance
  • 2001
    High-dimensional data inference for automobile insurance premia estimation
    Yoshua Bengio, Nicolas Chapados, Charles Dugas, Joumana Ghosn, Ichiro Takeuchi, Pascal Vincent · 2001 MITACS Annual General Meeting

Theses

  • 2009
    Sequential Machine Learning Approaches for Portfolio Management
    Nicolas Chapados · Université de Montréal
  • 2000
    Critères d'optimisation d'algorithmes d'apprentissage en gestion de portefeuille
    Nicolas Chapados · Université de Montréal

Working papers and technical reports

  • 2025
    Apriel-1.5-15B-Thinker: Mid-training is all you need
    Shruthan Radhakrishna, Aman Tiwari, Aanjaneya Shukla, Masoud Hashemi, Rishabh Maheshwary, Shiva Krishna Reddy Malay, Jash Mehta, Pulkit Pattnaik, Saloni Mittal, Khalil Slimi, Kelechi Ogueji, Akintunde Oladipo, Soham Parikh, Oluwanifemi Bamgbose, Toby Liang, Ahmed Masry, Khyati Mahajan, Sai Rajeswar Mudumba, Vikas Yadav, Sathwik Tejaswi Madhusudhan, Torsten Scholak, Sagar Davasam, Srinivas Sunkara, Nicolas Chapados · ServiceNow SLAM Lab Technical Report
  • 2024Conceptual illustration of open code models built from a large public code corpus
    StarCoder 2 and The Stack v2: The Next Generation
    Anton Lozhkov, Raymond Li, Loubna Ben Allal, Federico Cassano, Joel Lamy-Poirier, Nouamane Tazi, Ao Tang, Dmytro Pykhtar, Jiawei Liu, Yuxiang Wei, Tianyang Liu, Max Tian, Denis Kocetkov, Arthur Zucker, Younes Belkada, Zijian Wang, Qian Liu, Dmitry Abulkhanov, Indraneil Paul, Zhuang Li, Wen-Ding Li, Megan Risdal, Jia Li, Jian Zhu, Terry Yue Zhuo, Evgenii Zheltonozhskii, Nii Osae Osae Dade, Wenhao Yu, Lucas Krauß, Naman Jain, Yixuan Su, Xuanli He, Manan Dey, Edoardo Abati, Yekun Chai, Niklas Muennighoff, Xiangru Tang, Muhtasham Oblokulov, Christopher Akiki, Marc Marone, Chenghao Mou, Mayank Mishra, Alex Gu, Binyuan Hui, Tri Dao, Armel Zebaze, Olivier Dehaene, Nicolas Patry, Canwen Xu, Julian McAuley, Han Hu, Torsten Scholak, Sebastien Paquet, Jennifer Robinson, Carolyn Jane Anderson, Nicolas Chapados, Mostofa Patwary, Nima Tajbakhsh, Yacine Jernite, Carlos Muñoz Ferrandis, Lingming Zhang, Sean Hughes, Thomas Wolf, Arjun Guha, Leandro von Werra, Harm de Vries · BigCode Project Technical Report
  • 2023
    Can AI Read the Minds of Corporate Executives?
    Nicolas Chapados, Zhenzhen Fan, Ruslan Goyenko, Issam Hadj Laradji, Fred Liu, Chengyu Zhang · Preprint, Available at SSRN
  • 2018
    On the Importance of Attention in Meta-Learning for Few-Shot Text Classification
    Xiang Jiang, Mohammad Havaei, Gabriel Chartrand, Hassan Chouaib, Thomas Vincent, Andrew Jesson, Nicolas Chapados, Stan Matwin
  • 2013
    Volatility Forecasting and Explanatory Variables: A Tractable Bayesian Approach to Stochastic Volatility
    Nicolas Chapados, Christian Dorion · Working Paper
  • 2009
    Forecasting and Trading Commodity Contract Spreads with Gaussian Processes
    Nicolas Chapados, Yoshua Bengio · Working Paper
  • 2009
    Training Graphs of Learning Modules for Sequential Data
    Nicolas Chapados, Yoshua Bengio · Working Paper
  • 2003
    Comment améliorer la capacité de généralisation des algorithmes d'apprentissage pour la prise de décisions financières
    Nicolas Chapados · Cirano Scientific Series 2003s-20
  • 2003
    SAFIR: a Simple API for Financial Information Requests
    Nicolas Chapados · Cirano Scientific Series 2003s-21
  • 2002
    Valorisation d'options par optimisation du Sharpe Ratio
    Olivier Bardou, Yoshua Bengio, Nicolas Chapados, Réjean Ducharme · Cirano Scientific Series 2002s-47
  • 2001
    Extending Metric-Based Model Selection and Regularization in the Absence of Unlabeled Data
    Yoshua Bengio, Nicolas Chapados · Université de Montréal, département d'informatique et de recherche opérationnelle, Technical Report #1200

Patents

  • Trading schedule management system2019
    Pascal Bergeron, Nicolas Chapados, Étienne Marcotte, Marek Sabata, Ivan Sergienko, Richard Anthony Valenzano, Benjamin Crestel · WO 2020/051712 · CA 3,112,484
    Status: PCT application published 2020; Canadian application pending. US and European applications not pursued. · Google Patents
  • Covariate processing with neural network execution blocks2025
    Daniel Wong, Dmitri Carpov, Nicolas Chapados · US 12,406,173 · CA 3,097,644 · WO 2022/087745
    Status: Granted (US 2025, Canada 2023). Assignee: ServiceNow. · Google Patents
  • Method and system of demand forecasting for inventory management of slow-moving inventory in a supply chain (continuation)2024
    Nicolas Chapados · US 12,165,090
    Status: Granted 2024. Assignee: Blue Yonder. A further continuation is pending. · Google Patents
  • Method and system for generating synthetically anonymized data for a given task2023
    Florent Chandelier, Andrew Jesson, Lisa Di Jorio, Cécile Low-Kam, Florian Soudan, Mohammad Havaei, Nicolas Chapados · CA 3,105,533 · WO 2020/012439
    Status: Granted in Canada 2023. US and European applications not pursued. · Google Patents
  • Method and system of demand forecasting for inventory management of slow-moving inventory in a supply chain2022
    Nicolas Chapados · US 11,403,573
    Status: Granted 2022. Filed by JDA Software. · Google Patents
  • Method and system for processing a task with robustness to missing input information2021
    Nicolas Chapados, Nicolas Guizard, Mohammad Havaei, Yoshua Bengio · US 11,144,785 · CA 3,017,697 · WO 2017/158575
    Status: Granted (US 2021, Canada 2021). Filed by Imagia. · Google Patents
  • Method and apparatus for discourse management2002
    Nicolas Chapados, Peter Stubley, Claudia Pateras, Réal Tremblay · US 6,356,869
    Status: Granted 2002, expired 2019. Filed by Nortel Networks. Cited by 217 patent documents. · Google Patents