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Wei Huang
Wei Huang
Research Scientist, RIKEN AIP
Verified email at riken.jp - Homepage
Title
Cited by
Cited by
Year
On the neural tangent kernel of deep networks with orthogonal initialization
W Huang, W Du, RY Da Xu
IJCAI 2021, 2020
362020
Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective
W Huang, Y Li, W Du, RY Da Xu, J Yin, L Chen, M Zhang
ICLR 2022, 2021
342021
Augmentation-free graph contrastive learning
H Wang, J Zhang, Q Zhu, W Huang*
TMLR 2023, 2022
332022
Auto-scaling Vision Transformers without Training
W Chen, W Huang, X Du, X Song, Z Wang, D Zhou
ICLR 2022, 2022
322022
Deep Active Learning by Leveraging Training Dynamics
H Wang, W Huang, A Margenot, H Tong, J He
NeurIPS 2022, 2021
322021
Understanding and improving feature learning for out-of-distribution generalization
Y Chen*, W Huang*, K Zhou*, Y Bian, B Han, J Cheng
NeurIPS 2023, 2024
282024
Augmentation-free graph contrastive learning with performance guarantee
H Wang, J Zhang, Q Zhu, W Huang*
TMLR 2023, 2022
272022
On the Equivalence between Neural Network and Support Vector Machine
Y Chen, W Huang, LM Nguyen, TW Weng
NeurIPS 2021, 2021
262021
Earthfarsser: Versatile spatio-temporal dynamical systems modeling in one model
H Wu, Y Liang, W Xiong, Z Zhou, W Huang, S Wang, K Wang
AAAI 2024, 2024
242024
Critical percolation clusters in seven dimensions and on a complete graph
W Huang, P Hou, J Wang, RM Ziff, Y Deng
Physical Review E 97 (2), 022107, 2018
242018
Single-pass contrastive learning can work for both homophilic and heterophilic graph
H Wang, J Zhang, Q Zhu, W Huang, K Kawaguchi, X Xiao
arXiv preprint arXiv:2211.10890, 2022
22*2022
Pruning graph neural networks by evaluating edge properties
L Wang, W Huang, M Zhang, S Pan, X Chang, SW Su
Knowledge-Based Systems 256, 109847, 2022
182022
Adaptive multi-GPU exchange Monte Carlo for the 3D random field Ising model
CA Navarro, W Huang, Y Deng
Computer Physics Communications 205, 48-60, 2016
182016
Graph Lottery Ticket Automated
G Zhang, K Wang, W Huang, Y Yue, Y Wang, R Zimmermann, A Zhou, ...
ICLR 2024, 2023
132023
Global and Local Prompts Cooperation via Optimal Transport for Federated Learning
H Li, W Huang, J Wang, Y Shi
CVPR 2024, 2024
112024
Graph Neural Networks Provably Benefit from Structural Information: A Feature Learning Perspective
W Huang, Y Cao, H Wang, X Cao, T Suzuki
ICML 2023 HiLD Workshop (Oral), 2023
112023
Analyzing Deep PAC-Bayesian Learning with Neural Tangent Kernel: Convergence, Analytic Generalization Bound, and Efficient Hyperparameter Selection
W Huang, C Liu, Y Chen, RY Da Xu, M Zhang, TW Weng
Transactions on Machine Learning Research, 2023
11*2023
Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory
W Huang, Y Shi, Z Cai, T Suzuki
ICLR 2024, 2023
92023
Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis
W Chen, W Huang, X Gong, B Hanin, Z Wang
NeurIPS 2022, 2022
92022
Connection Sensitivity Matters for Training-free DARTS: From Architecture-Level Scoring to Operation-Level Sensitivity Analysis
M Zhang, W Huang, L Wang
arXiv preprint arXiv:2106.11542, 2021
9*2021
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