Thanh-Toan Do
31 papers · 2015–2026 · 12 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
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Research topics
Keywords
knowledge distillation
(4)
model compression
(3)
multimodal learning
(3)
bayesian neural network
(3)
data augmentation
(3)
variational inference
(2)
frequency domain
(2)
student model
(2)
deep learning
(2)
instance segmentation
(2)
posterior inference
(2)
probabilistic modeling
(2)
few-shot learning
(2)
image retrieval
(2)
optimal transport
(2)
generative model
(2)
latent dirichlet allocation
(1)
image segmentation
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embedding space
(1)
bayesian inference
(1)
Papers
Coverage-Constrained Human-AI Cooperation with Multiple Experts
AAAI 2026
Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models
ACL 2026
CamoFA: A Learnable Fourier-Based Augmentation for Camouflage Segmentation
WACV 2025
Enhancing Dataset Distillation via Non-Critical Region Refinement
CVPR 2025
MixLoRA-DSI: Dynamically Expandable Mixture-of-LoRA Experts for Rehearsal-Free Generative Retrieval over Dynamic Corpora
EMNLP 2025
Multi-Perspective Data Augmentation for Few-shot Object Detection
ICLR 2025
Preserving Clusters in Prompt Learning for Unsupervised Domain Adaptation
CVPR 2025
Probabilistic Learning to Defer: Handling Missing Expert Annotations and Controlling Workload Distribution
ICLR 2025
Frequency Attention for Knowledge Distillation
WACV 2024
Instance-dependent Noisy-label Learning with Graphical Model Based Noise-rate Estimation
ECCV 2024
Learning to Complement and to Defer to Multiple Users
ECCV 2024
MaskDiff: Modeling Mask Distribution with Diffusion Probabilistic Model for Few-Shot Instance Segmentation
AAAI 2024
MetaAug: Meta-Data Augmentation for Post-Training Quantization
ECCV 2024
Sharpness-Aware Data Generation for Zero-shot Quantization
ICML 2024
Collaborative Multi-Teacher Knowledge Distillation for Learning Low Bit-Width Deep Neural Networks
WACV 2023
Flat Seeking Bayesian Neural Networks
NeurIPS 2023
Instance-Dependent Noisy Label Learning via Graphical Modelling
WACV 2023
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning
NeurIPS 2023
Optimal Transport Model Distributional Robustness
NeurIPS 2023
Logic Rules Meet Deep Learning: A Novel Approach for Ship Type Classification (Extended Abstract)
IJCAI 2022
Probabilistic task modelling for meta-learning
UAI 2021
Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks
IJCAI 2020
Uncertainty in Model-Agnostic Meta-Learning using Variational Inference
WACV 2020
A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning
CVPR 2019
Bayesian Generative Active Deep Learning
ICML 2019
Compact Trilinear Interaction for Visual Question Answering
ICCV 2019
Scalable Place Recognition Under Appearance Change for Autonomous Driving
ICCV 2019
SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration Without Correspondences
CVPR 2019
Bayesian Semantic Instance Segmentation in Open Set World
ECCV 2018
Simultaneous Feature Aggregating and Hashing for Large-Scale Image Search
CVPR 2017
FAemb: A Function Approximation-Based Embedding Method for Image Retrieval
CVPR 2015