Toan Tran
18 papers · 2017–2025 · 7 conferences · across top CS/AI conferences
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NIPS (6)
ICLR (4)
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CVPR (2)
ICCV (2)
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ICML (1)
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Keywords
image generation
(3)
domain generalization
(3)
deep learning
(3)
bayesian inference
(2)
transfer learning
(2)
domain adaptation
(2)
generative model
(2)
diffusion model
(2)
data augmentation
(2)
multi-task learning
(1)
adversarial learning
(1)
active learning
(1)
probabilistic inference
(1)
variational inference
(1)
catastrophic forgetting
(1)
model aggregation
(1)
unsupervised domain adaptation
(1)
incremental learning
(1)
expectation maximization
(1)
representation learning
(1)
Papers
Boosting Multiple Views for pretrained-based Continual Learning
ICLR 2025
Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning
ICLR 2025
CASUAL: Conditional Support Alignment for Domain Adaptation with Label Shift
AAAI 2025
Tokens for Learning, Tokens for Unlearning: Mitigating Membership Inference Attacks in Large Language Models via Dual-Purpose Training
ACL 2025
Low-Rank Adaptation in Multilinear Operator Networks for Security-Preserving Incremental Learning
CVPR 2025
Supercharged One-step Text-to-Image Diffusion Models with Negative Prompts
ICCV 2025
On Inference Stability for Diffusion Models
AAAI 2024
Reducing Training Time in Cross-Silo Federated Learning Using Multigraph Topology
ICCV 2023
KL Guided Domain Adaptation
ICLR 2022
Learning Fractional White Noises in Neural Stochastic Differential Equations
NIPS 2022
Distributionally Robust Fair Principal Components via Geodesic Descents
ICLR 2022
Stochastic Multiple Target Sampling Gradient Descent
NIPS 2022
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources
NIPS 2021
Domain Invariant Representation Learning with Domain Density Transformations
NIPS 2021
Exploiting Domain-Specific Features to Enhance Domain Generalization
NIPS 2021
Bayesian Generative Active Deep Learning
ICML 2019
A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning
CVPR 2019
A Bayesian Data Augmentation Approach for Learning Deep Models
NIPS 2017