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Wei Huang
Wei Huang
Research Scientist, RIKEN AIP
Verified email at riken.jp - Homepage
Title
Cited by
Cited by
Year
Augmentation-free graph contrastive learning with performance guarantee
H Wang, J Zhang, Q Zhu, W Huang
TMLR 2023, 2022
442022
On the neural tangent kernel of deep networks with orthogonal initialization
W Huang, W Du, RY Da Xu
IJCAI 2021, 2020
262020
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
Auto-scaling Vision Transformers without Training
W Chen, W Huang, X Du, X Song, Z Wang, D Zhou
ICLR 2022, 2022
232022
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
212021
Deep Active Learning by Leveraging Training Dynamics
H Wang, W Huang, A Margenot, H Tong, J He
NeurIPS 2022, 2021
202021
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
20*2021
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
172016
On the Equivalence between Neural Network and Support Vector Machine
Y Chen, W Huang, LM Nguyen, TW Weng
NeurIPS 2021, Thirty-Fifth Conference on Neural Information Processing Systems, 2021
152021
Towards Understanding Feature Learning in Out-of-Distribution Generalization
Y Chen*, W Huang*, K Zhou*, Y Bian, B Han, J Cheng
NeurIPS 2023, 2023
112023
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
10*2022
Earthfarsser: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model
H Wu, Y Liang, W Xiong, Z Zhou, W Huang, S Wang, K Wang
Proceedings of the AAAI Conference on Artificial Intelligence 38 (14), 15906 …, 2024
72024
Mean field theory for deep dropout networks: digging up gradient backpropagation deeply
W Huang, RYD Xu, W Du, Y Zeng, Y Zhao
ECAI 2020, the 24th European Conference on Artificial Intelligence, 2020
72020
Deep relu networks have surprisingly simple polytopes
FL Fan, W Huang, X Zhong, L Ruan, T Zeng, H Xiong, F Wang
arXiv preprint arXiv:2305.09145, 2023
62023
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
6*2023
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
62022
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
52023
Implicit bias of deep linear networks in the large learning rate phase
W Huang, W Du, RY Da Xu, C Liu
arXiv preprint arXiv:2011.12547, 2020
5*2020
Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis
W Chen, W Huang, X Gong, B Hanin, Z Wang
NeurIPS 2022, 2022
42022
Gaussian process latent variable model factorization for context-aware recommender systems
W Huang, RY Da Xu
Pattern Recognition Letters 151, 281-287, 2021
42021
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