1 code implementation • 25 Mar 2024 • Jiawei Chen, Hongyu Lin, Xianpei Han, Yaojie Lu, Shanshan Jiang, Bin Dong, Le Sun
Then a superposition instance retriever is applied to retrieve corresponding instances of these superposition concepts from large-scale text corpus.
no code implementations • 20 Mar 2024 • Guoxiong Gao, Haocheng Ju, Jiedong Jiang, Zihan Qin, Bin Dong
In this paper, we present a semantic search engine for mathlib4 that accepts informal queries and finds the relevant theorems.
no code implementations • 17 Nov 2023 • Xinyu Xiao, Zhennan Zhou, Bin Dong, Dingjiong Ma, Li Zhou, Jie Sun
Non-linear effects in long-haul, high-speed optical fiber systems significantly hinder channel capacity.
1 code implementation • 3 Nov 2023 • Mingze Yuan, Peng Bao, Jiajia Yuan, Yunhao Shen, ZiFan Chen, Yi Xie, Jie Zhao, Yang Chen, Li Zhang, Lin Shen, Bin Dong
This has sparked significant interest in applying LLMs to enhance various aspects of healthcare, ranging from medical education to clinical decision support.
no code implementations • 22 Oct 2023 • Yifan Luo, Yiming Tang, Chengfeng Shen, Zhennan Zhou, Bin Dong
In this paper, we propose an optimal control framework tailored for multi-round interactions with LLMs.
1 code implementation • 18 Sep 2023 • Zhuoyuan Li, Bin Dong, Pingwen Zhang
Data assimilation is crucial in a wide range of applications, but it often faces challenges such as high computational costs due to data dimensionality and incomplete understanding of underlying mechanisms.
1 code implementation • 22 Aug 2023 • Bin Dong, Xuhua He, Pengfei Jin, Felix Schremmer, Qingchao Yu
We demonstrate that this framework has a potential to accelerate pure mathematical research, leading to the discovery of new conjectures and promising research directions that could otherwise take significant time to uncover.
no code implementations • 1 Aug 2023 • Hexin Dong, Jiawen Yao, Yuxing Tang, Mingze Yuan, Yingda Xia, Jian Zhou, Hong Lu, Jingren Zhou, Bin Dong, Le Lu, Li Zhang, Zaiyi Liu, Yu Shi, Ling Zhang
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer in which the tumor-vascular involvement greatly affects the resectability and, thus, overall survival of patients.
no code implementations • 26 Jul 2023 • Xiang Huang, Zhuoyuan Li, Hongsheng Liu, Zidong Wang, Hongye Zhou, Bin Dong, Bei Hua
Recently, using neural networks to simulate spatio-temporal dynamics has received a lot of attention.
no code implementations • 10 Jul 2023 • Mingze Yuan, Yingda Xia, Xin Chen, Jiawen Yao, Junli Wang, Mingyan Qiu, Hexin Dong, Jingren Zhou, Bin Dong, Le Lu, Li Zhang, Zaiyi Liu, Ling Zhang
In our experiments, the proposed method achieves a sensitivity of 85. 0% and specificity of 92. 6% for detecting gastric tumors on a hold-out test set consisting of 100 patients with cancer and 148 normal.
no code implementations • 29 May 2023 • ZiFan Chen, Jiazheng Li, Jie Zhao, Yiting Liu, Hongfeng Li, Bin Dong, Lei Tang, Li Zhang
This model consists of a proposing stage for coarse segmentation and a refining stage for improved segmentation, using two-way branches for enhanced performance and an up-down strategy for efficiency.
no code implementations • 25 May 2023 • Yifan Luo, Bin Dong
In this paper, we studied two identically-trained neural networks (i. e. networks with the same architecture, trained on the same dataset using the same algorithm, but with different initialization) and found that their outputs discrepancy on the training dataset exhibits a "double descent" phenomenon.
no code implementations • 16 May 2023 • Boxi Cao, Qiaoyu Tang, Hongyu Lin, Shanshan Jiang, Bin Dong, Xianpei Han, Jiawei Chen, Tianshu Wang, Le Sun
Memory is one of the most essential cognitive functions serving as a repository of world knowledge and episodes of activities.
no code implementations • CVPR 2023 • Mingze Yuan, Yingda Xia, Hexin Dong, ZiFan Chen, Jiawen Yao, Mingyan Qiu, Ke Yan, Xiaoli Yin, Yu Shi, Xin Chen, Zaiyi Liu, Bin Dong, Jingren Zhou, Le Lu, Ling Zhang, Li Zhang
Real-world medical image segmentation has tremendous long-tailed complexity of objects, among which tail conditions correlate with relatively rare diseases and are clinically significant.
no code implementations • 29 Mar 2023 • Ning Bian, Xianpei Han, Le Sun, Hongyu Lin, Yaojie Lu, Ben He, Shanshan Jiang, Bin Dong
(4) Can ChatGPT effectively leverage commonsense for answering questions?
1 code implementation • 7 Mar 2023 • Haocheng Ju, Haimiao Zhang, Lin Li, Xiao Li, Bin Dong
Joint channel estimation and signal detection (JCESD) in wireless communication systems is a crucial and challenging task, especially since it inherently poses a nonlinear inverse problem.
no code implementations • 27 Feb 2023 • Yiman Liu, Xiaoxiang Han, Tongtong Liang, Bin Dong, Jiajun Yuan, Menghan Hu, Qiaohong Liu, Jiangang Chen, Qingli Li, Yuqi Zhang
The EDMAE encoder is composed of a teacher and a student encoder.
no code implementations • 5 Feb 2023 • Yutong Xie, Minne Yuan, Bin Dong, Quanzheng Li
In supervised learning for image denoising, usually the paired clean images and noisy images are collected or synthesised to train a denoising model.
1 code implementation • 5 Dec 2022 • Pu Yang, Bin Dong
In this paper, we propose an alternating training framework for jointly learning a good pair of samplers and reconstructors via deep reinforcement learning (RL).
1 code implementation • Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence 2022 • Xiang Huang, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Min Wang, Haotian Chu, Jing Zhou, Fan Yu, Bei Hua, Bin Dong, Lei Chen
In recent years, deep learning technology has been used to solve partial differential equations (PDEs), among which the physics-informed neural networks (PINNs)method emerges to be a promising method for solving both forward and inverse PDE problems.
1 code implementation • 17 May 2022 • Hexin Dong, ZiFan Chen, Mingze Yuan, Yutong Xie, Jie Zhao, Fei Yu, Bin Dong, Li Zhang
Therefore, we propose a method called region-aware metric learning (RAML), which first separates the regions of the images and generates region-aware features for further metric learning.
no code implementations • 16 May 2022 • Wei Wan, Yuejin Zhang, Chenglong Bao, Bin Dong, Zuoqiang Shi
In this work, we propose a deep learning based method to solve the dynamic optimal transport in high dimensional space.
1 code implementation • 8 Apr 2022 • Weiguang Zhao, Chaolong Yang, Jianan Ye, Rui Zhang, Yuyao Yan, Xi Yang, Bin Dong, Amir Hussain, Kaizhu Huang
While weakly supervised multi-view face reconstruction (MVR) is garnering increased attention, one critical issue still remains open: how to effectively fuse multiple image information to reconstruct high-precision 3D models.
no code implementations • 24 Feb 2022 • Bin Dong
Computational imaging has been playing a vital role in the development of natural sciences.
1 code implementation • 8 Feb 2022 • Yutong Xie, Dufan Wu, Bin Dong, Quanzheng Li
We proved that a trained model in supervised deep learning minimizes the conditional risk for each input (Theorem 2. 1).
no code implementations • 10 Dec 2021 • Qi Sun, Hexin Dong, Zewei Chen, Jiacheng Sun, Zhenguo Li, Bin Dong
Gradient-based methods for the distributed training of residual networks (ResNets) typically require a forward pass of the input data, followed by back-propagating the error gradient to update model parameters, which becomes time-consuming as the network goes deeper.
1 code implementation • 9 Dec 2021 • Lufan Ma, Tiancai Wang, Bin Dong, Jiangpeng Yan, Xiu Li, Xiangyu Zhang
Our IFR enjoys several advantages: 1) simulates an infinite-depth refinement network while only requiring parameters of single residual block; 2) produces high-level equilibrium instance features of global receptive field; 3) serves as a plug-and-play general module easily extended to most object recognition frameworks.
no code implementations • 15 Nov 2021 • Xiang Huang, Zhanhong Ye, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Bingya Weng, Min Wang, Haotian Chu, Fan Yu, Bei Hua, Lei Chen, Bin Dong
Many important problems in science and engineering require solving the so-called parametric partial differential equations (PDEs), i. e., PDEs with different physical parameters, boundary conditions, shapes of computation domains, etc.
no code implementations • 2 Nov 2021 • Xiang Huang, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Bingya Weng, Min Wang, Haotian Chu, Jing Zhou, Fan Yu, Bei Hua, Lei Chen, Bin Dong
In recent years, deep learning technology has been used to solve partial differential equations (PDEs), among which the physics-informed neural networks (PINNs) emerges to be a promising method for solving both forward and inverse PDE problems.
no code implementations • 29 Sep 2021 • Hexin Dong, Fei Yu, Jie Zhao, Bin Dong, Li Zhang
This paper proposes an unsupervised cross-modality domain adaptation approach based on pixel alignment and self-training.
no code implementations • NeurIPS Workshop DLDE 2021 • Qi Sun, Hexin Dong, Zewei Chen, Weizhen Dian, Jiacheng Sun, Yitong Sun, Zhenguo Li, Bin Dong
Backpropagation algorithm is indispensable for training modern residual networks (ResNets) and usually tends to be time-consuming due to its inherent algorithmic lockings.
1 code implementation • 19 Jul 2021 • Dawei Du, Longyin Wen, Pengfei Zhu, Heng Fan, QinGhua Hu, Haibin Ling, Mubarak Shah, Junwen Pan, Ali Al-Ali, Amr Mohamed, Bakour Imene, Bin Dong, Binyu Zhang, Bouchali Hadia Nesma, Chenfeng Xu, Chenzhen Duan, Ciro Castiello, Corrado Mencar, Dingkang Liang, Florian Krüger, Gennaro Vessio, Giovanna Castellano, Jieru Wang, Junyu Gao, Khalid Abualsaud, Laihui Ding, Lei Zhao, Marco Cianciotta, Muhammad Saqib, Noor Almaadeed, Omar Elharrouss, Pei Lyu, Qi Wang, Shidong Liu, Shuang Qiu, Siyang Pan, Somaya Al-Maadeed, Sultan Daud Khan, Tamer Khattab, Tao Han, Thomas Golda, Wei Xu, Xiang Bai, Xiaoqing Xu, Xuelong Li, Yanyun Zhao, Ye Tian, Yingnan Lin, Yongchao Xu, Yuehan Yao, Zhenyu Xu, Zhijian Zhao, Zhipeng Luo, Zhiwei Wei, Zhiyuan Zhao
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint.
1 code implementation • NeurIPS 2021 • Bin Dong, Fangao Zeng, Tiancai Wang, Xiangyu Zhang, Yichen Wei
Moreover, the joint learning of unified query representation can greatly improve the detection performance of DETR.
Ranked #4 on Object Detection on COCO minival (AP75 metric)
2 code implementations • 7 May 2021 • Fangao Zeng, Bin Dong, Yuang Zhang, Tiancai Wang, Xiangyu Zhang, Yichen Wei
Temporal modeling of objects is a key challenge in multiple object tracking (MOT).
Ranked #1 on Multi-Object Tracking on MOT17 (e2e-MOT metric)
Multi-Object Tracking Multiple Object Tracking with Transformer +1
no code implementations • 9 Mar 2021 • Ce Wang, Haimiao Zhang, Qian Li, Kun Shang, Yuanyuan Lyu, Bin Dong, S. Kevin Zhou
More importantly, we show that using such a sinogram extrapolation module significantly improves the generalization capability of the model on unseen datasets (e. g., COVID-19 and LIDC datasets) when compared to existing approaches.
1 code implementation • 30 Nov 2020 • Haiwen Huang, Zhihan Li, Lulu Wang, Sishuo Chen, Bin Dong, Xinyu Zhou
Our analysis of the phenomenon reveals why our algorithm works.
Ranked #1 on Out-of-Distribution Detection on MS-1M vs. IJB-C
Out-of-Distribution Detection Out of Distribution (OOD) Detection
no code implementations • 30 Nov 2020 • Ti Bai, Biling Wang, Dan Nguyen, Bao Wang, Bin Dong, Wenxiang Cong, Mannudeep K. Kalra, Steve Jiang
However, there exists two challenges regarding the DL-based denoisers: 1) a trained model typically does not generate different image candidates with different noise-resolution tradeoffs which sometimes are needed for different clinical tasks; 2) the model generalizability might be an issue when the noise level in the testing images is different from that in the training dataset.
no code implementations • 28 Sep 2020 • Chizhou Liu, Yunzhen Feng, Ranran Wang, Bin Dong
Moreover, SWEEN models constructed using a few small models can achieve comparable performance to a single large model with a notable reduction in training time.
no code implementations • 3 Sep 2020 • Qi Sun, Hexin Dong, Zewei Chen, Weizhen Dian, Jiacheng Sun, Yitong Sun, Zhenguo Li, Bin Dong
Gradient-based algorithms for training ResNets typically require a forward pass of the input data, followed by back-propagating the objective gradient to update parameters, which are time-consuming for deep ResNets.
no code implementations • 24 Jul 2020 • Yunzhen Feng, Runtian Zhai, Di He, Li-Wei Wang, Bin Dong
Our experiments show that TD can provide fine-grained information for varied downstream tasks, and for the models trained from different initializations, the learned features are not the same in terms of downstream-task predictions.
no code implementations • 3 Jun 2020 • Junyu Liu, Zichao Long, Ranran Wang, Jie Sun, Bin Dong
To train the RODE-Net, we first estimate the parameters of the unknown RODE using the symbolic networks \cite{long2019pde} by solving a set of deterministic inverse problems based on the measured data, and use a generative adversarial network (GAN) to estimate the true distribution of the RODE's parameters.
no code implementations • 3 Jun 2020 • Ziju Shen, YuFei Wang, Dufan Wu, Xu Yang, Bin Dong
It is more desirable to design a personalized scanning strategy for each subject to obtain better reconstruction result.
no code implementations • 30 May 2020 • Haimiao Zhang, Baodong Liu, Hengyong Yu, Bin Dong
Other components, such as image priors and hyperparameters, are kept as the original design.
no code implementations • ICML Workshop AML 2021 • Chizhou Liu, Yunzhen Feng, Ranran Wang, Bin Dong
Moreover, SWEEN models constructed using a few small models can achieve comparable performance to a single large model with a notable reduction in training time.
1 code implementation • 10 Apr 2020 • Haidong Xie, Xueshuang Xiang, Naijin Liu, Bin Dong
The main idea of this approach is to use a cutoff-scale strategy to adaptively estimate a nonuniform budget to modify the AEs used in the training, ensuring that the strengths of the AEs are dynamically located in a reasonable range and ultimately improving the overall robustness of the AT model.
no code implementations • ICLR Workshop DeepDiffEq 2019 • Yiping Lu*, Zhuohan Li*, Di He, Zhiqing Sun, Bin Dong, Tao Qin, LiWei Wang, Tie-Yan Liu
In particular, how words in a sentence are abstracted into contexts by passing through the layers of the Transformer can be interpreted as approximating multiple particles' movement in the space using the Lie-Trotter splitting scheme and the Euler's method.
no code implementations • IJCNLP 2019 • Hongyu Lin, Yaojie Lu, Xianpei Han, Le Sun, Bin Dong, Shanshan Jiang
Current region-based NER models only rely on fully-annotated training data to learn effective region encoder, which often face the training data bottleneck.
no code implementations • WS 2019 • Yixuan Tong, Liang Liang, Boyan Liu, Shanshan Jiang, Bin Dong
This is the second time for SRCB to participate in WAT.
1 code implementation • 2 Oct 2019 • Bin Dong, Jikai Hou, Yiping Lu, Zhihua Zhang
Assuming that the teacher network is overparameterized, we argue that the teacher network is essentially harvesting dark knowledge from the data via early stopping.
no code implementations • 25 Sep 2019 • Bin Dong, Jikai Hou, Yiping Lu, Zhihua Zhang
Assuming that the teacher network is overparameterized, we argue that the teacher network is essentially harvesting dark knowledge from the data via early stopping.
no code implementations • 26 Jul 2019 • Fei Yu, Jie Zhao, Yanjun Gong, Zhi Wang, Yuxi Li, Fan Yang, Bin Dong, Quanzheng Li, Li Zhang
Segmenting coronary arteries is challenging, as classic unsupervised methods fail to produce satisfactory results and modern supervised learning (deep learning) requires manual annotation which is often time-consuming and can some time be infeasible.
no code implementations • 23 Jun 2019 • Haimiao Zhang, Bin Dong
More recently, as more data and computation resources are made available, deep learning based models (or deep models) pushed data-driven modeling to the extreme where the models are mostly based on learning with minimal human designs.
2 code implementations • ICLR 2020 • Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Li-Wei Wang, Tie-Yan Liu
In this paper, we provide a novel perspective towards understanding the architecture: we show that the Transformer can be mathematically interpreted as a numerical Ordinary Differential Equation (ODE) solver for a convection-diffusion equation in a multi-particle dynamic system.
no code implementations • 29 May 2019 • Pengfei Jin, Tianhao Lai, Rongjie Lai, Bin Dong
Designing appropriate convolution neural networks on manifold-structured point clouds can inherit and empower recent advances of CNNs to analyzing and processing point cloud data.
1 code implementation • 27 May 2019 • Yufei Wang, Ziju Shen, Zichao Long, Bin Dong
Conservation laws are considered to be fundamental laws of nature.
2 code implementations • NeurIPS 2019 • Dinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong
Adversarial training, typically formulated as a robust optimization problem, is an effective way of improving the robustness of deep networks.
no code implementations • 28 Jan 2019 • Bin Dong, Haocheng Ju, Yiping Lu, Zuoqiang Shi
For that, we introduce a new regularization by combining the low dimension manifold regularization with a higher order Curvature Regularization, and we call this new regularization CURE for short.
no code implementations • 3 Dec 2018 • Haimiao Zhang, Bin Dong, Baodong Liu
CT image reconstruction from incomplete data, such as sparse views and limited angle reconstruction, is an important and challenging problem in medical imaging.
2 code implementations • 30 Nov 2018 • Zichao Long, Yiping Lu, Bin Dong
Numerical experiments show that the PDE-Net 2. 0 has the potential to uncover the hidden PDE of the observed dynamics, and predict the dynamical behavior for a relatively long time, even in a noisy environment.
no code implementations • 31 May 2018 • Chenglong Bao, Jae Kyu Choi, Bin Dong
Quantitative susceptibility mapping (QSM) aims to visualize the three dimensional susceptibility distribution by solving the field-to-source inverse problem using the phase data in magnetic resonance signal.
no code implementations • 21 May 2018 • Stefan C. Schonsheck, Bin Dong, Rongjie Lai
PTC allows for the construction of compactly supported filters and is also robust to manifold deformations.
no code implementations • ICLR 2019 • Xiaoshuai Zhang, Yiping Lu, Jiaying Liu, Bin Dong
In this paper, we propose a new control framework called the moving endpoint control to restore images corrupted by different degradation levels in one model.
2 code implementations • 19 May 2018 • Haiwen Huang, Chang Wang, Bin Dong
NosAdam can be regarded as a fix to the non-convergence issue of Adam in alternative to the recent work of [Reddi et al., 2018].
no code implementations • ICLR 2018 • Dufan Wu, Kyungsang Kim, Bin Dong, Quanzheng Li
To align the acquisition with the annotations made by radiologists in the image domain, a DNN was built as the unrolled version of iterative reconstruction algorithms to map the acquisitions to images, and followed by a 3D convolutional neural network (CNN) to detect the abnormality in the reconstructed images.
no code implementations • 6 Nov 2017 • Dufan Wu, Kyungsang Kim, Bin Dong, Georges El Fakhri, Quanzheng Li
With 144 multi-slice fanbeam pro-jections, the proposed end-to-end detector could achieve comparable sensitivity with the reference detector, which was trained and applied on the fully-sampled image data.
no code implementations • ICML 2018 • Yiping Lu, Aoxiao Zhong, Quanzheng Li, Bin Dong
We show that many effective networks, such as ResNet, PolyNet, FractalNet and RevNet, can be interpreted as different numerical discretizations of differential equations.
5 code implementations • ICML 2018 • Zichao Long, Yiping Lu, Xianzhong Ma, Bin Dong
In this paper, we present an initial attempt to learn evolution PDEs from data.
no code implementations • 25 Jan 2017 • Jae Kyu Choi, Bin Dong, Xiaoqun Zhang
Wavelet frame systems are known to be effective in capturing singularities from noisy and degraded images.
1 code implementation • 7 Nov 2016 • Bin He, Bin Dong, Yi Guan, Jinfeng Yang, Zhipeng Jiang, Qiubin Yu, Jianyi Cheng, Chunyan Qu
Objective: To build a comprehensive corpus covering syntactic and semantic annotations of Chinese clinical texts with corresponding annotation guidelines and methods as well as to develop tools trained on the annotated corpus, which supplies baselines for research on Chinese texts in the clinical domain.
no code implementations • 17 Feb 2016 • Bin Dong, Zuowei Shen, Peichu Xie
In this paper, we introduce a generic wavelet frame based image restoration model, called the "general model", which includes most of the existing wavelet frame based models as special cases.