no code implementations • 28 Mar 2024 • Yishuai Cai, Shaowu Yang, Minglong Li, Xinglin Chen, Yunxin Mao, Xiaodong Yi, Wenjing Yang
Optimizing the morphologies and the controllers that adapt to various tasks is a critical issue in the field of robot design, aka.
1 code implementation • 20 Mar 2024 • Jingyi Wang, Xiaobo Xia, Long Lan, Xinghao Wu, Jun Yu, Wenjing Yang, Bo Han, Tongliang Liu
Given data with noisy labels, over-parameterized deep networks suffer overfitting mislabeled data, resulting in poor generalization.
no code implementations • 23 Jan 2024 • Zhen Liang, Taoran Wu, Ran Zhao, Bai Xue, Ji Wang, Wenjing Yang, Shaojun Deng, Wanwei Liu
However, these strategies face challenges in addressing the "unknown dilemma" concerning whether the exact output region or the introduced approximation error violates the property in question.
no code implementations • 27 Nov 2023 • Xiang Li, Long Lan, Husam Lahza, Shaowu Yang, Shuihua Wang, Wenjing Yang, Hengzhu Liu, Yudong Zhang
EAFP-Med can efficiently extract lesion features from various medical images based on prompts, enhancing the model's performance.
1 code implementation • 27 Jun 2023 • Zhen Liang, Dejin Ren, Bai Xue, Ji Wang, Wenjing Yang, Wanwei Liu
Moreover, for NNs that do not feature these properties with respect to the input set, we explore subsets of the input set for establishing the local homeomorphism property and then abandon these subsets for reachability computations.
no code implementations • 11 May 2023 • Jing Zhao, Heliang Zheng, Chaoyue Wang, Long Lan, Wanrong Huang, Wenjing Yang
Specifically, we proposed two disturbance methods, i. e., Rollback disturbance (Back-D) and Image disturbance (Image-D), to construct misalignment between the noisy images used for predicting null-text guidance and text guidance (subsequently referred to as \textbf{null-text noisy image} and \textbf{text noisy image} respectively) in the sampling process.
1 code implementation • 5 May 2023 • Zhen Liang, Taoran Wu, Changyuan Zhao, Wanwei Liu, Bai Xue, Wenjing Yang, Ji Wang
For the fine-tuning repair process, BIRDNN analyzes the behavior differences of neurons on positive and negative samples to identify the most responsible neurons for the erroneous behaviors.
no code implementations • ICCV 2023 • Jing Zhao, Heliang Zheng, Chaoyue Wang, Long Lan, Wenjing Yang
The advent of open-source AI communities has produced a cornucopia of powerful text-guided diffusion models that are trained on various datasets.
no code implementations • ICCV 2023 • Haotian Wang, Haoang Chi, Wenjing Yang, Zhipeng Lin, Mingyang Geng, Long Lan, Jing Zhang, DaCheng Tao
As a complementary of SDPA, we also propose Target-Combined Deployment Authorization (TPDA), where unauthorized domains are partially accessible, and simplify the DSO method to a perturbation operation on the pseudo predictions, referred to as Target-Dependent Domain-Specified Optimization (TDSO).
no code implementations • 2 Dec 2022 • Zhen Liang, Changyuan Zhao, Wanwei Liu, Bai Xue, Wenjing Yang, Zhengbin Pang
Based on Koopman operator theory, this paper presents an alternative perspective of linear dynamics on dealing with the credit assignment problem for trained neural networks.
1 code implementation • 9 Oct 2022 • Zhen Liang, Dejin Ren, Wanwei Liu, Ji Wang, Wenjing Yang, Bai Xue
The homeomorphism property exists in some widely used NNs such as invertible NNs.
1 code implementation • 20 Sep 2022 • Mingkun Wang, Xinge Zhu, Changqian Yu, Wei Li, Yuexin Ma, Ruochun Jin, Xiaoguang Ren, Dongchun Ren, Mingxu Wang, Wenjing Yang
In view of this, we propose a new goal area-based framework, named Goal Area Network (GANet), for motion forecasting, which models goal areas rather than exact goal coordinates as preconditions for trajectory prediction, performing more robustly and accurately.
Ranked #15 on Motion Forecasting on Argoverse CVPR 2020
no code implementations • 11 Jun 2022 • Wenjing Yang, Ganghua Wang, Jie Ding, Yuhong Yang
One problem is understanding if a network is more compressible than another of the same structure.
no code implementations • 7 Jun 2022 • Jinkai Tian, Xiaoyu Sun, Yuxuan Du, Shanshan Zhao, Qing Liu, Kaining Zhang, Wei Yi, Wanrong Huang, Chaoyue Wang, Xingyao Wu, Min-Hsiu Hsieh, Tongliang Liu, Wenjing Yang, DaCheng Tao
Due to the intrinsic probabilistic nature of quantum mechanics, it is reasonable to postulate that quantum generative learning models (QGLMs) may surpass their classical counterparts.
no code implementations • NeurIPS 2021 • Longqi Yang, Liangliang Zhang, Wenjing Yang
This paper studies a long-standing problem of learning the representations of a whole graph without human supervision.
1 code implementation • NeurIPS 2021 • Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Bo Han, William K. Cheung, James T. Kwok
To this end, we propose a target orientated hypothesis adaptation network (TOHAN) to solve the FHA problem, where we generate highly-compatible unlabeled data (i. e., an intermediate domain) to help train a target-domain classifier.
1 code implementation • ICCV 2021 • Yunrui Guo, Guglielmo Camporese, Wenjing Yang, Alessandro Sperduti, Lamberto Ballan
In this way, we are able to control the compactness of the features of the same class around the center of the gaussians, thus controlling the ability of the classifier in detecting samples from unknown classes.
1 code implementation • ICLR 2022 • Haoang Chi, Feng Liu, Bo Han, Wenjing Yang, Long Lan, Tongliang Liu, Gang Niu, Mingyuan Zhou, Masashi Sugiyama
In this paper, we demystify assumptions behind NCD and find that high-level semantic features should be shared among the seen and unseen classes.
no code implementations • 22 Jan 2021 • Dehong Gao, Wenjing Yang, Huiling Zhou, Yi Wei, Yi Hu, Hao Wang
The majority of current MTL studies adopt the hard parameter sharing structure, where hard layers tend to learn general representations over all tasks and specific layers are prone to learn specific representations for each task.
1 code implementation • WS 2020 • Dehong Gao, Wenjing Yang, Huiling Zhou, Yi Wei, Yi Hu, Hao Wang
In e-commerce system, category prediction is to automatically predict categories of given texts.
no code implementations • 17 Aug 2019 • Jingwen Wang, Hao Zhang, Cheng Zhang, Wenjing Yang, Liqun Shao, Jie Wang
To overcome this obstacle, we present NDORGS (Numerous Documents' Overview Report Generation Scheme) that integrates text filtering, keyword scoring, single-document summarization (SDS), topic modeling, MDS, and title generation to generate a coherent, well-structured ORPT.
no code implementations • 25 Nov 2018 • Bo Zhang, Bin Chen, Jinyu Yang, Wenjing Yang, Jiankang Zhang
Motivated by Shannon's model and recent rehabilitation of self-supervised artificial intelligence having a "World Model", this paper propose an unified intelligence-communication (UIC) model for describing a single agent and any multi-agent system.