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Thang Doan
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2020 – today
- 2024
- [c12]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: 1555-1563 - [c11]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. CVPR 2024: 4187-4196 - [i20]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 abs/2403.06295 (2024) - [i19]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 abs/2406.05271 (2024) - 2023
- [c10]Thang Doan, Seyed-Iman Mirzadeh, Mehrdad Farajtabar:
Continual Learning Beyond a Single Model. CoLLAs 2023: 961-991 - [c9]Jean-Baptiste Gaya, Thang Doan, Lucas Caccia, Laure Soulier, Ludovic Denoyer, Roberta Raileanu:
Building a Subspace of Policies for Scalable Continual Learning. ICLR 2023 - [i18]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 abs/2306.14291 (2023) - [i17]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 abs/2307.11227 (2023) - [i16]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 abs/2308.00310 (2023) - 2022
- [j2]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: 597-636 (2022) - [i15]Thang Doan, Seyed-Iman Mirzadeh, Joelle Pineau, Mehrdad Farajtabar:
Efficient Continual Learning Ensembles in Neural Network Subspaces. CoRR abs/2202.09826 (2022) - [i14]Jean-Baptiste Gaya, Thang Doan, Lucas Caccia, Laure Soulier, Ludovic Denoyer, Roberta Raileanu:
Building a Subspace of Policies for Scalable Continual Learning. CoRR abs/2211.10445 (2022) - 2021
- [j1]Moloud Abdar
, Maryam Samami, Sajjad Dehghani Mahmoodabad, Thang Doan, Bogdan Mazoure, Reza Hashemifesharaki, Li Liu, Abbas Khosravi
Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning. Comput. Biol. Medicine 135: 104418 (2021) - [c8]Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier:
A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix. AISTATS 2021: 1072-1080 - [c7]Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau:
Regularized Inverse Reinforcement Learning. ICLR 2021 - [i13]Bonnie Li, Vincent François-Lavet, Thang Doan, Joelle Pineau:
Domain Adversarial Reinforcement Learning. CoRR abs/2102.07097 (2021) - 2020
- [c6]Bogdan Mazoure, Remi Tachet des Combes, Thang Doan, Philip Bachman, R. Devon Hjelm:
Deep Reinforcement and InfoMax Learning. NeurIPS 2020 - [i12]Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup, Guillaume Rabusseau:
Provably efficient reconstruction of policy networks. CoRR abs/2002.02863 (2020) - [i11]Bogdan Mazoure, Remi Tachet des Combes, Thang Doan, Philip Bachman, R. Devon Hjelm:
Deep Reinforcement and InfoMax Learning. CoRR abs/2006.07217 (2020) - [i10]Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau:
Regularized Inverse Reinforcement Learning. CoRR abs/2010.03691 (2020) - [i9]Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier:
A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix. CoRR abs/2010.04003 (2020)
2010 – 2019
- 2019
- [c5]Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
On-Line Adaptative Curriculum Learning for GANs. AAAI 2019: 3470-3477 - [c4]Bogdan Mazoure, Thang Doan, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Leveraging exploration in off-policy algorithms via normalizing flows. CoRL 2019: 430-444 - [c3]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: 202-211 - [i8]Thang Doan, Neil Veira, Brian Keng:
Generating Realistic Sequences of Customer-level Transactions for Retail Datasets. CoRR abs/1901.05577 (2019) - [i7]Isabela Albuquerque, João Monteiro, Thang Doan, Breandan Considine, Tiago H. Falk, Ioannis Mitliagkas:
Multi-objective training of Generative Adversarial Networks with multiple discriminators. CoRR abs/1901.08680 (2019) - [i6]Bogdan Mazoure, Thang Doan, Audrey Durand, R. Devon Hjelm, Joelle Pineau:
Leveraging exploration in off-policy algorithms via normalizing flows. CoRR abs/1905.06893 (2019) - [i5]Srinivas Venkattaramanujam, Eric Crawford, Thang Doan, Doina Precup:
Self-supervised Learning of Distance Functions for Goal-Conditioned Reinforcement Learning. CoRR abs/1907.02998 (2019) - [i4]Thang Doan, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning. CoRR abs/1909.07543 (2019) - 2018
- [c2]Thang Doan, Neil Veira, Brian Keng:
Generating Realistic Sequences of Customer-Level Transactions for Retail Datasets. ICDM Workshops 2018: 820-827 - [c1]Bogdan Mazoure, Thang Doan, Saibal Ray:
EmojiGAN: learning emojis distributions with a generative model. WASSA@EMNLP 2018: 273-279 - [i3]Thang Doan, Bogdan Mazoure, Clare Lyle:
GAN Q-learning. CoRR abs/1805.04874 (2018) - [i2]Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Online Adaptative Curriculum Learning for GANs. CoRR abs/1808.00020 (2018) - 2017
- [i1]Peter Henderson, Thang Doan, Riashat Islam, David Meger:
Bayesian Policy Gradients via Alpha Divergence Dropout Inference. CoRR abs/1712.02037 (2017)
Coauthor Index
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last updated on 2024-10-04 20:02 CEST by the dblp team
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