1 code implementation • 4 Jan 2022 • Yuning You, Tianlong Chen, Zhangyang Wang, Yang shen
Accordingly, we have extended the prefabricated discrete prior in the augmentation set, to a learnable continuous prior in the parameter space of graph generators, assuming that graph priors per se, similar to the concept of image manifolds, can be learned by data generation.
no code implementations • NeurIPS 2021 • Xiu-Shen Wei, Yang shen, Xuhao Sun, Han-Jia Ye, Jian Yang
Specifically, based on the captured visual representations by attention, we develop an encoder-decoder structure network of a reconstruction task to unsupervisedly distill high-level attribute-specific vectors from the appearance-specific visual representations without attribute annotations.
no code implementations • 18 Oct 2021 • Yang shen, Bin Zou
We consider a mean-variance portfolio selection problem in a financial market with contagion risk.
no code implementations • ICLR 2022 • Yuning You, Yue Cao, Tianlong Chen, Zhangyang Wang, Yang shen
Optimizing an objective function with uncertainty awareness is well-known to improve the accuracy and confidence of optimization solutions.
1 code implementation • 15 Jul 2021 • Yang shen, Sanjoy Dasgupta, Saket Navlakha
We discovered a two layer neural circuit in the fruit fly olfactory system that addresses this challenge by uniquely combining sparse coding and associative learning.
1 code implementation • 24 Jun 2021 • Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang shen
Designing novel protein sequences for a desired 3D topological fold is a fundamental yet non-trivial task in protein engineering.
2 code implementations • 10 Jun 2021 • Yuning You, Tianlong Chen, Yang shen, Zhangyang Wang
Unfortunately, unlike its counterpart on image data, the effectiveness of GraphCL hinges on ad-hoc data augmentations, which have to be manually picked per dataset, by either rules of thumb or trial-and-errors, owing to the diverse nature of graph data.
no code implementations • 11 Jan 2021 • Yang shen, Bin Zou
By introducing a deterministic auxiliary process defined forward in time, we formulate an alternative time-consistent problem related to the original MV problem, and obtain the optimal strategy and the value function to the new problem in closed-form.
no code implementations • 1 Jan 2021 • Yue Cao, Tianlong Chen, Zhangyang Wang, Yang shen
Optimizing an objective function with uncertainty awareness is well-known to improve the accuracy and confidence of optimization solutions.
no code implementations • 14 Nov 2020 • Yuning You, Yang shen
Compound-protein pairs dominate FDA-approved drug-target pairs and the prediction of compound-protein affinity and contact (CPAC) could help accelerate drug discovery.
2 code implementations • NeurIPS 2020 • Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang shen
In this paper, we propose a graph contrastive learning (GraphCL) framework for learning unsupervised representations of graph data.
1 code implementation • ICML 2020 • Yuning You, Tianlong Chen, Zhangyang Wang, Yang shen
We first elaborate three mechanisms to incorporate self-supervision into GCNs, analyze the limitations of pretraining & finetuning and self-training, and proceed to focus on multi-task learning.
1 code implementation • 16 Apr 2020 • Mostafa Karimi, Arman Hasanzadeh, Yang shen
We have developed the first deep generative model for drug combination design, by jointly embedding graph-structured domain knowledge and iteratively training a reinforcement learning-based chemical graph-set designer.
2 code implementations • CVPR 2020 • Yuning You, Tianlong Chen, Zhangyang Wang, Yang shen
Graph convolution networks (GCN) are increasingly popular in many applications, yet remain notoriously hard to train over large graph datasets.
no code implementations • 29 Dec 2019 • Mostafa Karimi, Di wu, Zhangyang Wang, Yang shen
DeepRelations shows superior interpretability to the state-of-the-art: without compromising affinity prediction, it boosts the AUPRC of contact prediction 9. 5, 16. 9, 19. 3 and 5. 7-fold for the test, compound-unique, protein-unique, and both-unique sets, respectively.
no code implementations • 28 Dec 2019 • Yue Cao, Yang shen
Moreover, estimating model quality, also known as the quality assessment problem, is rarely addressed in protein docking.
1 code implementation • NeurIPS 2019 • Yue Cao, Tianlong Chen, Zhangyang Wang, Yang shen
Learning to optimize has emerged as a powerful framework for various optimization and machine learning tasks.
1 code implementation • 31 Jan 2019 • Yue Cao, Yang shen
To the best of our knowledge, this study represents the first uncertainty quantification solution for protein docking, with theoretical rigor and comprehensive assessment.
no code implementations • ECCV 2018 • Yang Shen, Bingbing Ni, Zefan Li, Ning Zhuang
Predicting future activities from an egocentric viewpoint is of particular interest in assisted living.
2 code implementations • 20 Jun 2018 • Mostafa Karimi, Di wu, Zhangyang Wang, Yang shen
Motivation: Drug discovery demands rapid quantification of compound-protein interaction (CPI).
no code implementations • 20 Mar 2017 • Weiyao Lin, Yang shen, Junchi Yan, Mingliang Xu, Jianxin Wu, Jingdong Wang, Ke Lu
We first introduce a boosting-based approach to learn a correspondence structure which indicates the patch-wise matching probabilities between images from a target camera pair.
1 code implementation • ICCV 2015 • Yang Shen, Weiyao Lin, Junchi Yan, Mingliang Xu, Jianxin Wu, Jingdong Wang
This paper addresses the problem of handling spatial misalignments due to camera-view changes or human-pose variations in person re-identification.