Tianyang Hu
25 papers · 2021–2025 · 12 conferences · across top CS/AI conferences
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Conferences
ICML (5)
NIPS (4)
ICLR (3)
AISTATS (2)
CVPR (2)
ICCV (2)
JMLR (2)
ECCV (1)
EMNLP (1)
IJCAI (1)
NAACL (1)
UAI (1)
Top co-authors
Keywords
contrastive learning
(3)
representation learning
(3)
deep neural network
(2)
overparametrized neural network
(2)
image generation
(2)
domain generalization
(2)
decision boundary
(2)
curse of dimensionality
(2)
out-of-distribution generalization
(2)
pretrained model
(2)
diffusion model
(2)
knowledge distillation
(2)
diffusion distillation
(2)
neural tangent kernel
(2)
chain-of-thought reasoning
(1)
data augmentation
(1)
text-to-image synthesis
(1)
learning theory
(1)
self-supervised learning
(1)
symbolic reasoning
(1)
Papers
Minimax Optimal Deep Neural Network Classifiers Under Smooth Decision Boundary
JMLR 2025
Elucidating the design space of language models for image generation
ICML 2025
Understanding the Language Model to Solve the Symbolic Multi-Step Reasoning Problem from the Perspective of Buffer Mechanism
EMNLP 2025
Learning Few-Step Diffusion Models by Trajectory Distribution Matching
ICCV 2025
Adding Additional Control to One-Step Diffusion with Joint Distribution Matching
ICCV 2025
Getting More Juice Out of Your Data: Hard Pair Refinement Enhances Visual-Language Models Without Extra Data
NAACL 2025
You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANs
ICLR 2025
Accelerating Diffusion Sampling with Optimized Time Steps
CVPR 2024
JointDreamer: Ensuring Geometry Consistency and Text Congruence in Text-to-3D Generation via Joint Score Distillation
ECCV 2024
Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers
ICML 2024
Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion
ICML 2024
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling
ICML 2024
Elucidating the design space of classifier-guided diffusion generation
ICLR 2024
Deciphering the Projection Head: Representation Evaluation Self-supervised Learning
IJCAI 2024
Random Smoothing Regularization in Kernel Gradient Descent Learning
JMLR 2024
Exact Count of Boundary Pieces of ReLU Classifiers: Towards the Proper Complexity Measure for Classification
UAI 2023
Complexity Matters: Rethinking the Latent Space for Generative Modeling
NIPS 2023
Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models
NIPS 2023
Inducing Neural Collapse in Deep Long-tailed Learning
AISTATS 2023
ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-Real Novel View Synthesis via Contrastive Learning
CVPR 2023
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding
ICLR 2023
Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization
ICML 2023
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization
NIPS 2022
Understanding Square Loss in Training Overparametrized Neural Network Classifiers
NIPS 2022
Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network
AISTATS 2021