Yang Shen

According to our database, Yang Shen authored at least 31 papers between 2005 and 2024.

Collaborative distances:

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

2024

Correlational Lagrangian Schrödinger Bridge: Learning Dynamics with Population-Level Regularization.

Yuning You, Ruida Zhou, Yang Shen

CoRR, 2024

2023

Graph Contrastive Learning: An Odyssey towards Generalizable, Scalable and Principled Representation Learning on Graphs.

Yan Han, Yuning You, Wenqing Zheng, Scott Hoang, Tianxin Wei, Majdi Hassan, Tianlong Chen, Ying Ding, Yang Shen, Zhangyang Wang

IEEE Data Eng. Bull., 2023

Graph Domain Adaptation via Theory-Grounded Spectral Regularization.

Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Guest Editorial Special Section on Learning With Multimodal Data for Biomedical Informatics.

Zhangyang Wang, Vishal Patel, Bing Yao, Steve B. Jiang, Huimin Lu, Yang Shen

IEEE Trans. Circuits Syst. Video Technol., 2022

Predicting protein structure from single sequences.

Yang Shen

Nat. Comput. Sci., 2022

Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations.

Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative.

Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang

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

Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How.

Yuning You, Yue Cao, Tianlong Chen, Zhangyang Wang, Yang Shen

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Explainable Deep Relational Networks for Predicting Compound-Protein Affinities and Contacts.

Mostafa Karimi, Di Wu, Zhangyang Wang, Yang Shen

J. Chem. Inf. Model., 2021

TALE: Transformer-based protein function Annotation with joint sequence-Label Embedding.

Yue Cao, Yang Shen

Bioinform., 2021

Graph Contrastive Learning Automated.

Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang

Proceedings of the 38th International Conference on Machine Learning, 2021

Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design.

Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

De Novo Protein Design for Novel Folds Using Guided Conditional Wasserstein Generative Adversarial Networks.

Mostafa Karimi, Shaowen Zhu, Yue Cao, Yang Shen

J. Chem. Inf. Model., 2020

Cross-Modality Protein Embedding for Compound-Protein Affinity and Contact Prediction.

Yuning You, Yang Shen

CoRR, 2020

L^2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks.

Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

CoRR, 2020

Network-principled deep generative models for designing drug combinations as graph sets.

Mostafa Karimi, Arman Hasanzadeh, Yang Shen

Bioinform., 2020

Graph Contrastive Learning with Augmentations.

Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen

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

When Does Self-Supervision Help Graph Convolutional Networks?

Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

Proceedings of the 37th International Conference on Machine Learning, 2020

L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks.

Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Energy-based Graph Convolutional Networks for Scoring Protein Docking Models.

Yue Cao, Yang Shen

CoRR, 2019

Bayesian active learning for optimization and uncertainty quantification in protein docking.

Yue Cao, Yang Shen

CoRR, 2019

DeepAffinity: interpretable deep learning of compound-protein affinity through unified recurrent and convolutional neural networks.

Mostafa Karimi, Di Wu, Zhangyang Wang, Yang Shen

Bioinform., 2019

Learning to Optimize in Swarms.

Yue Cao, Tianlong Chen, Zhangyang Wang, Yang Shen

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural Networks.

Mostafa Karimi, Di Wu, Zhangyang Wang, Yang Shen

CoRR, 2018

iCFN: an efficient exact algorithm for multistate protein design.

Mostafa Karimi, Yang Shen

Bioinform., 2018

2017

Biomedical informatics with optimization and machine learning.

Thomas S. Huang, Jiayu Zhou, Zhangyang Wang, Qing Ling, Yang Shen

EURASIP J. Bioinform. Syst. Biol., 2017

2008

Protein Docking by the Underestimation of Free Energy Funnels in the Space of Encounter Complexes.

Yang Shen, Ioannis Ch. Paschalidis, Pirooz Vakili, Sandor Vajda

PLoS Comput. Biol., 2008

2007

SDU: A Semidefinite Programming-Based Underestimation Method for Stochastic Global Optimization in Protein Docking.

Ioannis Ch. Paschalidis, Yang Shen, Pirooz Vakili, Sandor Vajda

IEEE Trans. Autom. Control., 2007

Optimizing noisy funnel-like functions on the euclidean group with applications to protein docking.

Yang Shen, Pirooz Vakili, Sandor Vajda, Ioannis Ch. Paschalidis

Proceedings of the 46th IEEE Conference on Decision and Control, 2007

2006

Protein-protein docking with reduced potentials by exploiting multi-dimensional energy funnels.

Ioannis Ch. Paschalidis, Yang Shen, Pirooz Vakili, Sandor Vajda

Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006

2005

A Semi-Definite programming-based Underestimation method for global optimization in molecular docking.

Ioannis Ch. Paschalidis, Yang Shen, Sandor Vajda, Pirooz Vakili

Proceedings of the 44th IEEE IEEE Conference on Decision and Control and 8th European Control Conference Control, 2005