1 code implementation • 24 Dec 2024 • Yang shen, Xiu-Shen Wei, Yifan Sun, Yuxin Song, Tao Yuan, Jian Jin, Heyang Xu, Yazhou Yao, Errui Ding
In this paper, we explore the idea that CV adopts discrete and terminological task definitions (\eg, ``image segmentation''), which may be a key barrier to zero-shot task generalization.
1 code implementation • 6 Dec 2024 • Jian Jin, Yang shen, ZhenYong Fu, Jian Yang
Customized generation aims to incorporate a novel concept into a pre-trained text-to-image model, enabling new generations of the concept in novel contexts guided by textual prompts.
no code implementations • 17 Nov 2024 • Lei Yang, Xinyu Zhang, Jun Li, Chen Wang, Zhiying Song, Tong Zhao, Ziying Song, Li Wang, Mo Zhou, Yang shen, Kai Wu, Chen Lv
Previous studies have demonstrated the effectiveness of cooperative perception in extending the perception range and overcoming occlusions, thereby improving the safety of autonomous driving.
1 code implementation • 26 Oct 2024 • Jiwoong Park, Yang shen
How can diffusion models process 3D geometries in a coarse-to-fine manner, akin to our multiscale view of the world?
no code implementations • 19 Oct 2024 • Andrew Fleck, Edward Furman, Yang shen
In order to properly manage risk, practitioners must understand the aggregate risks they are exposed to.
no code implementations • 3 Jul 2024 • Len Patrick Dominic M. Garces, Yang shen
We assume that a power utility investor is ambiguity-averse, with the preference to robustness captured by the homothetic multiplier robust specification, and the investor's investment and consumption strategies are constrained to closed convex sets.
no code implementations • 4 Feb 2024 • Yuning You, Ruida Zhou, Yang shen
Accurate modeling of system dynamics holds intriguing potential in broad scientific fields including cytodynamics and fluid mechanics.
1 code implementation • 29 Jan 2024 • Lei Yang, Xinyu Zhang, Jun Li, Li Wang, Chuang Zhang, Li Ju, Zhiwei Li, Yang shen
Our method surpasses all previous methods by a significant margin in new scenes, including +42. 57% for vehicle, +5. 87% for pedestrian, and +14. 89% for cyclist compared to BEVHeight on the DAIR-V2X-I heterologous benchmark.
no code implementations • 4 Jan 2024 • Qiang Zhang, Ruida Zhou, Yang shen, Tie Liu
This paper considers the problem of offline optimization, where the objective function is unknown except for a collection of ``offline" data examples.
1 code implementation • 30 Nov 2023 • Tengjin Weng, Yang shen, Zhidong Zhao, Zhiming Cheng, Shuai Wang
Optic disc and cup segmentation plays a crucial role in automating the screening and diagnosis of optic glaucoma.
1 code implementation • 21 Nov 2023 • Xiu-Shen Wei, Yang shen, Xuhao Sun, Peng Wang, Yuxin Peng
Our work focuses on tackling large-scale fine-grained image retrieval as ranking the images depicting the concept of interests (i. e., the same sub-category labels) highest based on the fine-grained details in the query.
no code implementations • 17 Nov 2023 • Shuai Wang, Tengjin Weng, Jingyi Wang, Yang shen, Zhidong Zhao, Yixiu Liu, Pengfei Jiao, Zhiming Cheng, Yaqi Wang
Medical image segmentation annotations exhibit variations among experts due to the ambiguous boundaries of segmented objects and backgrounds in medical images.
no code implementations • 20 Oct 2023 • Xinyu Zhang, Li Wang, Zhiqiang Jiang, Kun Dai, Tao Xie, Lei Yang, Wenhao Yu, Yang shen, Jun Li
However, these methods only integrate long-range context information among keypoints with a fixed receptive field, which constrains the network from reconciling the importance of features with different receptive fields to realize complete image perception, hence limiting the matching accuracy.
2 code implementations • 14 Oct 2023 • Jiabei He, Yang shen, Xiu-Shen Wei, Ye Wu
However, the absence of a unified open-source software library covering various paradigms in FGIR poses a significant challenge for researchers and practitioners in the field.
no code implementations • 15 Sep 2023 • Marinka Zitnik, Michelle M. Li, Aydin Wells, Kimberly Glass, Deisy Morselli Gysi, Arjun Krishnan, T. M. Murali, Predrag Radivojac, Sushmita Roy, Anaïs Baudot, Serdar Bozdag, Danny Z. Chen, Lenore Cowen, Kapil Devkota, Anthony Gitter, Sara Gosline, Pengfei Gu, Pietro H. Guzzi, Heng Huang, Meng Jiang, Ziynet Nesibe Kesimoglu, Mehmet Koyuturk, Jian Ma, Alexander R. Pico, Nataša Pržulj, Teresa M. Przytycka, Benjamin J. Raphael, Anna Ritz, Roded Sharan, Yang shen, Mona Singh, Donna K. Slonim, Hanghang Tong, Xinan Holly Yang, Byung-Jun Yoon, Haiyuan Yu, Tijana Milenković
Network biology is an interdisciplinary field bridging computational and biological sciences that has proved pivotal in advancing the understanding of cellular functions and diseases across biological systems and scales.
no code implementations • 26 Jul 2023 • Zhenxiao Yin, Xiaobing Dai, Zewen Yang, Yang shen, Georges Hattab, Hang Zhao
The growing demand for accurate control in varying and unknown environments has sparked a corresponding increase in the requirements for power supply components, including permanent magnet synchronous motors (PMSMs).
no code implementations • 21 Jun 2023 • Hao Xu, Jia Liu, Yang shen, Kenan Lou, Yanxia Bao, Ruihua Zhang, Shuyue Zhou, Hongsen Zhao, Shuai Wang
However, by analyzing the statistical characteristic of activated units after pooling, we found that a large number of units dropped by sorting pooling are negative-value units that contain useful information and can contribute considerably to the final decision.
no code implementations • 5 Jun 2023 • Tengjin Weng, Yang shen, Kai Jin, Zhiming Cheng, Yunxiang Li, Gewen Zhang, Shuai Wang, Yaqi Wang
Specifically, we use points to annotate fluid regions in unlabeled OCT images and the Superpixel-Guided Pseudo-Label Generation (SGPLG) module generates pseudo-labels and pixel-level label trust maps from the point annotations.
3 code implementations • CVPR 2023 • Yang shen, Xuhao Sun, Xiu-Shen Wei
The learning objective of these methods can be summarized as mapping the learned feature representations to the samples' label space.
no code implementations • 18 Mar 2023 • Junjie Ye, Xuanting Chen, Nuo Xu, Can Zu, Zekai Shao, Shichun Liu, Yuhan Cui, Zeyang Zhou, Chao Gong, Yang shen, Jie zhou, Siming Chen, Tao Gui, Qi Zhang, Xuanjing Huang
GPT series models, such as GPT-3, CodeX, InstructGPT, ChatGPT, and so on, have gained considerable attention due to their exceptional natural language processing capabilities.
no code implementations • 7 Feb 2023 • Xiu-Shen Wei, Xuhao Sun, Yang shen, Anqi Xu, Peng Wang, Faen Zhang
Simplicity Bias (SB) is a phenomenon that deep neural networks tend to rely favorably on simpler predictive patterns but ignore some complex features when applied to supervised discriminative tasks.
Ranked #4 on
Long-tail Learning
on CIFAR-10-LT (ρ=10)
4 code implementations • The European Conference on Computer Vision (ECCV) 2022 • Hao Chen, Xiu-Shen Wei, Faen Zhang, Yang shen, Hui Xu, Liang Xiao
Automatic Check-Out (ACO) aims to accurately predict the presence and count of each category of products in check-out images, where a major challenge is the significant domain gap between training data (single-product exemplars) and test data (check-out images).
1 code implementation • 7 Oct 2022 • Tianxin Wei, Yuning You, Tianlong Chen, Yang shen, Jingrui He, Zhangyang Wang
This paper targets at improving the generalizability of hypergraph neural networks in the low-label regime, through applying the contrastive learning approach from images/graphs (we refer to it as HyperGCL).
4 code implementations • 28 Sep 2022 • Yang shen, Xuhao Sun, Xiu-Shen Wei, Qing-Yuan Jiang, Jian Yang
In this paper, we propose Suppression-Enhancing Mask based attention and Interactive Channel transformatiON (SEMICON) to learn binary hash codes for dealing with large-scale fine-grained image retrieval tasks.
3 code implementations • IEEE International Conference on Multimedia and Expo (ICME) 2022 • Yang shen, Xuhao Sun, Xiu-Shen Wei, Hanxu Hu, Zhipeng Chen
In this paper, we propose a simple but effective method for dealing with the challenging fine-grained cross-modal retrieval task where it aims to enable flexible retrieval among subor-dinate categories across different modalities.
no code implementations • 31 May 2022 • Yang shen, Bin Zou
We consider monotone mean-variance (MMV) portfolio selection problems with a conic convex constraint under diffusion models, and their counterpart problems under mean-variance (MV) preferences.
1 code implementation • IJCAI 2022 • Yu-Yan Xu, Yang shen, Xiu-Shen Wei, Jian Yang
The task of webly-supervised fne-grained recognition is to boost recognition accuracy of classifying subordinate categories (e. g., different bird species)by utilizing freely available but noisy web data. As the label noises signifcantly hurt the network training, it is desirable to distinguish and eliminate noisy images.
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.
1 code implementation • 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.
4 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).
Ranked #2 on
Drug Discovery
on BindingDB IC50
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.