Detecting and removing multiplicative spatial bias in high-throughput screening technologies. - Iurie Caraus; Bogdan Mazoure; Robert Nadon; Vladimir Makarenkov (Bioinform., 2017)

Alpha-Divergences in Variational Dropout. - Bogdan Mazoure; Riashat Islam (CoRR, 2017)

EmojiGAN: learning emojis distributions with a generative model. - Bogdan Mazoure; Thang Doan; Saibal Ray (WASSA@EMNLP, 2018)

GAN Q-learning. - Thang Doan; Bogdan Mazoure; Clare Lyle (CoRR, 2018)

Online Adaptative Curriculum Learning for GANs. - Thang Doan; João Monteiro 002; Isabela Albuquerque; Bogdan Mazoure; Audrey Durand; Joelle Pineau; R. Devon Hjelm (CoRR, 2018)

On-Line Adaptative Curriculum Learning for GANs. - Thang Doan; João Monteiro 002; Isabela Albuquerque; Bogdan Mazoure; Audrey Durand; Joelle Pineau; R. Devon Hjelm (AAAI, 2019)

Leveraging exploration in off-policy algorithms via normalizing flows. - Bogdan Mazoure; Thang Doan; Audrey Durand; Joelle Pineau; R. Devon Hjelm (CoRL, 2019)

Exploring Attention Mechanism for Acoustic-based Classification of Speech Utterances into System-directed and Non-system-directed. - Atta Norouzian; Bogdan Mazoure; Dermot Connolly; Daniel Willett (ICASSP, 2019)

An intelligent shopping list based on the application of partitioning and machine learning algorithms. - Nadia Tahiri; Bogdan Mazoure; Vladimir Makarenkov (SciPy, 2019)

Learning Gaussian Graphical Models with Ordered Weighted L1 Regularization. - Cody Mazza-Anthony; Bogdan Mazoure; Mark Coates (CoRR, 2019)

Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning. - Thang Doan; Bogdan Mazoure; Audrey Durand; Joelle Pineau; R. Devon Hjelm (CoRR, 2019)

Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning. - Tianyu Li; Bogdan Mazoure; Doina Precup; Guillaume Rabusseau (AISTATS, 2020)

Deep Reinforcement and InfoMax Learning. - Bogdan Mazoure; Remi Tachet des Combes; Thang Doan; Philip Bachman; R. Devon Hjelm (NeurIPS, 2020)

Provably efficient reconstruction of policy networks. - Bogdan Mazoure; Thang Doan; Tianyu Li; Vladimir Makarenkov; Joelle Pineau; Doina Precup; Guillaume Rabusseau (CoRR, 2020)

A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix. - Thang Doan; Mehdi Abbana Bennani; Bogdan Mazoure; Guillaume Rabusseau; Pierre Alquier (AISTATS, 2021)

Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning. - Moloud Abdar; Maryam Samami; Sajjad Dehghani Mahmoodabad; Thang Doan; Bogdan Mazoure; Reza Hashemifesharaki; Li Liu 002; Abbas Khosravi; U. Rajendra Acharya; Vladimir Makarenkov; Saeid Nahavandi (Comput. Biol. Medicine, 2021)

Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Offline RL. - Bogdan Mazoure; Paul Mineiro; Pavithra Srinath; Reza Sharifi Sedeh; Doina Precup; Adith Swaminathan (CoRR, 2021)

Learning Gaussian Graphical Models With Ordered Weighted $ ell _1$ Regularization. - Cody Mazza-Anthony; Bogdan Mazoure; Mark Coates (IEEE Trans. Signal Process., 2021)

Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL. - Bogdan Mazoure; Ahmed M. Ahmed 004; R. Devon Hjelm; Andrey Kolobov; Patrick MacAlpine (ICLR, 2022)

Improving Zero-Shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions. - Bogdan Mazoure; Ilya Kostrikov; Ofir Nachum; Jonathan Tompson (NeurIPS, 2022)

The Sandbox Environment for Generalizable Agent Research (SEGAR). - R. Devon Hjelm; Bogdan Mazoure; Florian Golemo; Felipe Frujeri; Mihai Jalobeanu; Andrey Kolobov (CoRR, 2022)

Sequential Density Estimation via NCWFAs Sequential Density Estimation via Nonlinear Continuous Weighted Finite Automata. - Tianyu Li; Bogdan Mazoure; Guillaume Rabusseau (CoRR, 2022)

Low-Rank Representation of Reinforcement Learning Policies. - Bogdan Mazoure; Thang Doan; Tianyu Li; Vladimir Makarenkov; Joelle Pineau; Doina Precup; Guillaume Rabusseau (J. Artif. Intell. Res., 2022)

Contrastive Value Learning: Implicit Models for Simple Offline RL. - Bogdan Mazoure; Benjamin Eysenbach; Ofir Nachum; Jonathan Tompson (CoRL, 2023)

Learning About Progress From Experts. - Jake Bruce; Ankit Anand; Bogdan Mazoure; Rob Fergus (ICLR, 2023)

Accelerating exploration and representation learning with offline pre-training. - Bogdan Mazoure; Jake Bruce; Doina Precup; Rob Fergus; Ankit Anand (CoRR, 2023)

Value function estimation using conditional diffusion models for control. - Bogdan Mazoure; Walter Talbott; Miguel Ángel Bautista 001; R. Devon Hjelm; Alexander Toshev; Joshua M. Susskind (CoRR, 2023)

Large Language Models as Generalizable Policies for Embodied Tasks. - Andrew Szot; Max Schwarzer; Harsh Agrawal; Bogdan Mazoure; Walter Talbott; Katherine Metcalf; Natalie Mackraz; R. Devon Hjelm; Alexander Toshev (CoRR, 2023)

Large Language Models as Generalizable Policies for Embodied Tasks. - Andrew Szot; Max Schwarzer; Harsh Agrawal; Bogdan Mazoure; Rin Metcalf; Walter Talbott; Natalie Mackraz; R. Devon Hjelm; Alexander T. Toshev (ICLR, 2024)

Grounding Multimodal Large Language Models in Actions. - Andrew Szot; Bogdan Mazoure; Harsh Agrawal; R. Devon Hjelm; Zsolt Kira; Alexander Toshev (NeurIPS, 2024)

On the benefits of pixel-based hierarchical policies for task generalization. - Tudor Cristea-Platon; Bogdan Mazoure; Josh Susskind; Walter Talbott (CoRR, 2024)

From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons. - Andrew Szot; Bogdan Mazoure; Omar Attia; Aleksei Timofeev; Harsh Agrawal; R. Devon Hjelm; Zhe Gan; Zsolt Kira; Alexander Toshev (CVPR, 2025)

On the Modeling Capabilities of Large Language Models for Sequential Decision Making. - Martin Klissarov; R. Devon Hjelm; Alexander T. Toshev; Bogdan Mazoure (ICLR, 2025)