Thang Doan

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 33

Top Topics

Attraction Repulsion

Bayesian Nonparametric

Orthogonal Projection

Reinforcement Learning

Top Venues

Publications

Thang Doan, Sima Behpour, Xin Li, Wenbin He, Liang Gou, Liu Ren
A streamlined Approach to Multimodal Few-Shot Class Incremental Learning for Fine-Grained Datasets. CoRR (2024)
Xiaoqi Wang, Wenbin He, Xiwei Xuan, Clint Sebastian, Jorge Piazentin Ono, Xin Li, Sima Behpour, Thang Doan, Liang Gou, Han-Wei Shen, Liu Ren
USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation. CoRR (2024)
Thang Doan, Xin Li, Sima Behpour, Wenbin He, Liang Gou, Liu Ren
Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection. AAAI (2024)
Xin Li, Sima Behpour, Thang Doan, Wenbin He, Liang Gou, Liu Ren
UP-DP: Unsupervised Prompt Learning for Data Pre-Selection with Vision-Language Models. CoRR (2023)
Sima Behpour, Thang Doan, Xin Li, Wenbin He, Liang Gou, Liu Ren
GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients. CoRR (2023)
Thang Doan, Seyed-Iman Mirzadeh, Mehrdad Farajtabar
Continual Learning Beyond a Single Model. CoLLAs (2023)
Thang Doan, Xin Li, Sima Behpour, Wenbin He, Liang Gou, Liu Ren
Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection. CoRR (2023)
Jean-Baptiste Gaya, Thang Doan, Lucas Caccia, Laure Soulier, Ludovic Denoyer, Roberta Raileanu
Building a Subspace of Policies for Scalable Continual Learning. ICLR (2023)
Thang Doan, Seyed-Iman Mirzadeh, Joelle Pineau, Mehrdad Farajtabar
Efficient Continual Learning Ensembles in Neural Network Subspaces. CoRR (2022)
Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup, Guillaume Rabusseau
Low-Rank Representation of Reinforcement Learning Policies. J. Artif. Intell. Res. 75 (2022)
Jean-Baptiste Gaya, Thang Doan, Lucas Caccia, Laure Soulier, Ludovic Denoyer, Roberta Raileanu
Building a Subspace of Policies for Scalable Continual Learning. CoRR (2022)
Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier
A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix. AISTATS (2021)
Moloud Abdar, Maryam Samami, Sajjad Dehghani Mahmoodabad, Thang Doan, Bogdan Mazoure, Reza Hashemifesharaki, Li Liu, Abbas Khosravi, U. Rajendra Acharya, Vladimir Makarenkov, Saeid Nahavandi
Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning. Comput. Biol. Medicine 135 (2021)
Bonnie Li, Vincent François-Lavet, Thang Doan, Joelle Pineau
Domain Adversarial Reinforcement Learning. CoRR (2021)
Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau
Regularized Inverse Reinforcement Learning. ICLR (2021)
Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau
Regularized Inverse Reinforcement Learning. CoRR (2020)
Bogdan Mazoure, Remi Tachet des Combes, Thang Doan, Philip Bachman, R. Devon Hjelm
Deep Reinforcement and InfoMax Learning. NeurIPS (2020)
Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier
A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix. CoRR (2020)
Bogdan Mazoure, Remi Tachet des Combes, Thang Doan, Philip Bachman, R. Devon Hjelm
Deep Reinforcement and InfoMax Learning. CoRR (2020)
Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup, Guillaume Rabusseau
Provably efficient reconstruction of policy networks. CoRR (2020)
Isabela Albuquerque, João Monteiro, Thang Doan, Breandan Considine, Tiago H. Falk, Ioannis Mitliagkas
Multi-objective training of Generative Adversarial Networks with multiple discriminators. CoRR (2019)
Bogdan Mazoure, Thang Doan, Audrey Durand, Joelle Pineau, R. Devon Hjelm
Leveraging exploration in off-policy algorithms via normalizing flows. CoRL (2019)
Bogdan Mazoure, Thang Doan, Audrey Durand, R. Devon Hjelm, Joelle Pineau
Leveraging exploration in off-policy algorithms via normalizing flows. CoRR (2019)
Isabela Albuquerque, João Monteiro, Thang Doan, Breandan Considine, Tiago H. Falk, Ioannis Mitliagkas
Multi-objective training of Generative Adversarial Networks with multiple discriminators. ICML (2019)
Thang Doan, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning. CoRR (2019)
Srinivas Venkattaramanujam, Eric Crawford, Thang Doan, Doina Precup
Self-supervised Learning of Distance Functions for Goal-Conditioned Reinforcement Learning. CoRR (2019)
Thang Doan, Neil Veira, Brian Keng
Generating Realistic Sequences of Customer-level Transactions for Retail Datasets. CoRR (2019)
Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm
On-Line Adaptative Curriculum Learning for GANs. AAAI (2019)
Thang Doan, Bogdan Mazoure, Clare Lyle
GAN Q-learning. CoRR (2018)
Bogdan Mazoure, Thang Doan, Saibal Ray
EmojiGAN: learning emojis distributions with a generative model. WASSA@EMNLP (2018)
Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm
Online Adaptative Curriculum Learning for GANs. CoRR (2018)
Thang Doan, Neil Veira, Brian Keng
Generating Realistic Sequences of Customer-Level Transactions for Retail Datasets. ICDM Workshops (2018)
Peter Henderson, Thang Doan, Riashat Islam, David Meger
Bayesian Policy Gradients via Alpha Divergence Dropout Inference. CoRR (2017)