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Tung Pham 0001
Person information
- affiliation: VinAI Research, Vietnam
Other persons with the same name
- Tung Pham — disambiguation page
- Tung Pham 0002
— University of Innsbruck, Dornbirn, Austria
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2020 – today
- 2024
- [c10]Tran Huynh, Dang Nguyen, Tung Pham, Anh Tran:
COMBAT: Alternated Training for Effective Clean-Label Backdoor Attacks. AAAI 2024: 2436-2444 - [i13]Anh Bui, Vy Vo, Tung Pham, Dinh Q. Phung, Trung Le:
Diversity-Aware Agnostic Ensemble of Sharpness Minimizers. CoRR abs/2403.13204 (2024) - 2023
- [i12]Ngoc N. Tran, Son Duong, Hoang Phan, Tung Pham, Dinh Q. Phung, Trung Le:
Sharpness & Shift-Aware Self-Supervised Learning. CoRR abs/2305.10252 (2023) - [i11]Tuan Truong, Hoang-Phi Nguyen, Tung Pham, Minh-Tuan Tran, Mehrtash Harandi, Dinh Phung, Trung Le:
RSAM: Learning on manifolds with Riemannian Sharpness-aware Minimization. CoRR abs/2309.17215 (2023) - [i10]Ngoc N. Tran, Lam Tran, Hoang Phan, Anh Tuan Bui, Tung Pham, Toan Tran, Dinh Q. Phung, Trung Le:
Robust Contrastive Learning With Theory Guarantee. CoRR abs/2311.09671 (2023) - 2022
- [c9]Khang Le, Huy Nguyen, Khai Nguyen, Tung Pham, Nhat Ho:
On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity. AISTATS 2022: 4397-4413 - [c8]Khang Le, Dung Q. Le, Huy Nguyen, Dat Do, Tung Pham, Nhat Ho:
Entropic Gromov-Wasserstein between Gaussian Distributions. ICML 2022: 12164-12203 - [c7]Khai Nguyen, Dang Nguyen, Quoc Dinh Nguyen, Tung Pham, Hung Bui, Dinh Phung, Trung Le, Nhat Ho:
On Transportation of Mini-batches: A Hierarchical Approach. ICML 2022: 16622-16655 - [c6]Khai Nguyen, Dang Nguyen, The-Anh Vu-Le, Tung Pham, Nhat Ho:
Improving Mini-batch Optimal Transport via Partial Transportation. ICML 2022: 16656-16690 - 2021
- [c5]Trung Nguyen, Quang-Hieu Pham, Tam Le, Tung Pham, Nhat Ho, Binh-Son Hua:
Point-set Distances for Learning Representations of 3D Point Clouds. ICCV 2021: 10458-10467 - [c4]Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui:
Distributional Sliced-Wasserstein and Applications to Generative Modeling. ICLR 2021 - [c3]Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui:
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein. ICLR 2021 - [c2]Khang Le, Huy Nguyen, Quang Minh Nguyen, Tung Pham, Hung Bui, Nhat Ho:
On Robust Optimal Transport: Computational Complexity and Barycenter Computation. NeurIPS 2021: 21947-21959 - [i9]Trung Nguyen, Quang-Hieu Pham, Tam Le, Tung Pham, Nhat Ho, Binh-Son Hua:
Point-set Distances for Learning Representations of 3D Point Clouds. CoRR abs/2102.04014 (2021) - [i8]Khai Nguyen, Quoc Nguyen, Nhat Ho, Tung Pham, Hung Bui, Dinh Phung, Trung Le:
BoMb-OT: On Batch of Mini-batches Optimal Transport. CoRR abs/2102.05912 (2021) - [i7]Khang Le, Huy Nguyen, Quang Nguyen, Nhat Ho, Tung Pham, Hung Bui:
On Robust Optimal Transport: Computational Complexity, Low-rank Approximation, and Barycenter Computation. CoRR abs/2102.06857 (2021) - [i6]Khang Le, Huy Nguyen, Tung Pham, Nhat Ho:
On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity. CoRR abs/2108.07992 (2021) - [i5]Khai Nguyen, Dang Nguyen, Tung Pham, Nhat Ho:
An Efficient Mini-batch Method via Partial Transportation. CoRR abs/2108.09645 (2021) - [i4]Khang Le, Dung Le, Huy Nguyen, Dat Do, Tung Pham, Nhat Ho:
Entropic Gromov-Wasserstein between Gaussian Distributions. CoRR abs/2108.10961 (2021) - 2020
- [c1]Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui:
On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm. ICML 2020: 7673-7682 - [i3]Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui:
On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm. CoRR abs/2002.03293 (2020) - [i2]Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui:
Distributional Sliced-Wasserstein and Applications to Generative Modeling. CoRR abs/2002.07367 (2020) - [i1]Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui:
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein. CoRR abs/2010.01787 (2020)
Coauthor Index
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last updated on 2024-08-16 18:29 CEST by the dblp team
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