Yaochen Xie

According to our database, Yaochen Xie authored at least 23 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Genetic InfoMax: Exploring Mutual Information Maximization in High-Dimensional Imaging Genetics Studies.

Yaochen Xie, Ziqian Xie, Sheikh Muhammad Saiful Islam, Degui Zhi, Shuiwang Ji

Trans. Mach. Learn. Res., 2024

SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains.

Ran Xu, Hui Liu, Sreyashi Nag, Zhenwei Dai, Yaochen Xie, Xianfeng Tang, Chen Luo, Yang Li, Joyce C. Ho, Carl Yang, Qi He

CoRR, 2024

Exploring Query Understanding for Amazon Product Search.

Chen Luo, Xianfeng Tang, Hanqing Lu, Yaochen Xie, Hui Liu, Zhenwei Dai, Limeng Cui, Ashutosh Joshi, Sreyashi Nag, Yang Li, Zhen Li, Rahul Goutam, Jiliang Tang, Haiyang Zhang, Qi He

CoRR, 2024

3D Molecular Geometry Analysis with 2D Graphs.

Zhao Xu, Yaochen Xie, Youzhi Luo, Xuan Zhang, Xinyi Xu, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji

Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations.

Xuan Zhang, Jacob Helwig, Yuchao Lin, Yaochen Xie, Cong Fu, Stephan Wojtowytsch, Shuiwang Ji

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Group Contrastive Self-Supervised Learning on Graphs.

Xinyi Xu, Cheng Deng, Yaochen Xie, Shuiwang Ji

IEEE Trans. Pattern Anal. Mach. Intell., March, 2023

Self-Supervised Learning of Graph Neural Networks: A Unified Review.

Yaochen Xie, Zhao Xu, Jingtun Zhang, Zhengyang Wang, Shuiwang Ji

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.

Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji

CoRR, 2023

2022

Augmented Equivariant Attention Networks for Microscopy Image Transformation.

Yaochen Xie, Yu Ding, Shuiwang Ji

IEEE Trans. Medical Imaging, 2022

Task-Agnostic Graph Explanations.

Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward W. Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Frontiers of Graph Neural Networks with DIG.

Shuiwang Ji, Meng Liu, Yi Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Zhao Xu, Haiyang Yu

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Self-Supervised Representation Learning via Latent Graph Prediction.

Yaochen Xie, Zhao Xu, Shuiwang Ji

Proceedings of the International Conference on Machine Learning, 2022

2021

Global voxel transformer networks for augmented microscopy.

Zhengyang Wang, Yaochen Xie, Shuiwang Ji

Nat. Mach. Intell., 2021

DIG: A Turnkey Library for Diving into Graph Deep Learning Research.

Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora Oztekin, Xuan Zhang, Shuiwang Ji

J. Mach. Learn. Res., 2021

Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs.

Zhao Xu, Youzhi Luo, Xuan Zhang, Xinyi Xu, Yaochen Xie, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji

CoRR, 2021

Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks.

Meng Liu, Cong Fu, Xuan Zhang, Limei Wang, Yaochen Xie, Hao Yuan, Youzhi Luo, Zhao Xu, Shenglong Xu, Shuiwang Ji

CoRR, 2021

Self-Supervised Learning of Graph Neural Networks: A Unified Review.

Yaochen Xie, Zhao Xu, Zhengyang Wang, Shuiwang Ji

CoRR, 2021

2020

zhengyang-wang/GVTNets: Code for "Global Voxel Transformer Networks for Augmented Microscopy".

Zhengyang Wang, Yaochen Xie, Shuiwang Ji

Dataset, November, 2020

MoleculeKit: Machine Learning Methods for Molecular Property Prediction and Drug Discovery.

Zhengyang Wang, Meng Liu, Youzhi Luo, Zhao Xu, Yaochen Xie, Limei Wang, Lei Cai, Shuiwang Ji

CoRR, 2020

Augmented Equivariant Attention Networks for Electron Microscopy Image Super-Resolution.

Yaochen Xie, Yu Ding, Shuiwang Ji

CoRR, 2020

Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising.

Yaochen Xie, Zhengyang Wang, Shuiwang Ji

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Finding the Stars in the Fireworks: Deep Understanding of Motion Sensor Fingerprint.

Xiangyang Li, Huiqi Liu, Lan Zhang, Zhenan Wu, Yaochen Xie, Ge Chen, Chunxiao Wan, Zhongwei Liang

IEEE/ACM Trans. Netw., 2019

2018

Finding the Stars in the Fireworks: Deep Understanding of Motion Sensor Fingerprint.

Huiqi Liu, Xiangyang Li, Lan Zhang, Yaochen Xie, Zhenan Wu, Qian Dai, Ge Chen, Chunxiao Wan

Proceedings of the 2018 IEEE Conference on Computer Communications, 2018