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Weilin Cong
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2020 – today
- 2024
- [i11]Weilin Cong, Jian Kang
, Hanghang Tong, Mehrdad Mahdavi:
On the Generalization Capability of Temporal Graph Learning Algorithms: Theoretical Insights and a Simpler Method. CoRR abs/2402.16387 (2024) - [i10]Limei Wang, Kaveh Hassani, Si Zhang, Dongqi Fu, Baichuan Yuan, Weilin Cong, Zhigang Hua, Hao Wu, Ning Yao, Bo Long:
Learning Graph Quantized Tokenizers for Transformers. CoRR abs/2410.13798 (2024) - 2023
- [j2]Ryan Tan
Understanding the Structural Components Behind the Psychological Effects of Autonomous Sensory Meridian Response (ASMR) With Machine Learning and Experimental Methods. J. Media Psychol. Theor. Methods Appl. 35(3): 181-189 (2023) - [c10]Weilin Cong, Mehrdad Mahdavi:
Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection. AISTATS 2023: 6674-6703 - [c9]Weilin Cong, Si Zhang, Jian Kang
Do We Really Need Complicated Model Architectures For Temporal Networks? ICLR 2023 - [c8]Xiao Lin, Jian Kang
BeMap: Balanced Message Passing for Fair Graph Neural Network. LoG 2023: 37 - [c7]Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Chun-cheng Jason Chen, Mehrdad Mahdavi:
DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability. SDM 2023: 442-450 - [i9]Weilin Cong, Mehrdad Mahdavi:
Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection. CoRR abs/2302.08990 (2023) - [i8]Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi:
Do We Really Need Complicated Model Architectures For Temporal Networks? CoRR abs/2302.11636 (2023) - [i7]Xiao Lin, Jian Kang, Weilin Cong, Hanghang Tong:
BeMap: Balanced Message Passing for Fair Graph Neural Network. CoRR abs/2306.04107 (2023) - 2022
- [j1]Huaipan Jiang
Predicting Protein-Ligand Docking Structure with Graph Neural Network. J. Chem. Inf. Model. 62(12): 2923-2932 (2022) - [c6]Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam:
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks. ICLR 2022 - 2021
- [c5]Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi:
On Provable Benefits of Depth in Training Graph Convolutional Networks. NeurIPS 2021: 9936-9949 - [i6]Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi:
On the Importance of Sampling in Learning Graph Convolutional Networks. CoRR abs/2103.02696 (2021) - [i5]Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi:
On Provable Benefits of Depth in Training Graph Convolutional Networks. CoRR abs/2110.15174 (2021) - [i4]Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam:
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks. CoRR abs/2111.08202 (2021) - [i3]Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Mehrdad Mahdavi, Chun-cheng Jason Chen:
Dynamic Graph Representation Learning via Graph Transformer Networks. CoRR abs/2111.10447 (2021) - 2020
- [c4]Weilin Cong, Rana Forsati, Mahmut T. Kandemir, Mehrdad Mahdavi:
Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks. KDD 2020: 1393-1403 - [c3]Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Anand Sivasubramaniam, Mahmut T. Kandemir:
GCN meets GPU: Decoupling "When to Sample" from "How to Sample". NeurIPS 2020 - [c2]Dule Shu, Weilin Cong, Jiaming Chai, Conrad S. Tucker:
Encrypted rich-data steganography using generative adversarial networks. WiseML@WiSec 2020: 55-60 - [i2]Weilin Cong, Rana Forsati, Mahmut T. Kandemir, Mehrdad Mahdavi:
Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks. CoRR abs/2006.13866 (2020)
2010 – 2019
- 2019
- [c1]Wei Liu, Weilin Cong, Chengyu Hu, Peng Lu, Jinmei Lai:
Balance of memory footprint and runtime for high-density routing in large-scale FPGAs. ASICON 2019: 1-4 - 2017
- [i1]Weilin Cong, Sanyuan Zhao, Hui Tian, Jianbing Shen:
Improved Face Detection and Alignment using Cascade Deep Convolutional Network. CoRR abs/1707.09364 (2017)
Coauthor Index
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