no code implementations • 26 Feb 2024 • Kexin Chen, Yuyang Du, Tao You, Mobarakol Islam, Ziyu Guo, Yueming Jin, Guangyong Chen, Pheng-Ann Heng
We further design an adaptive weight assignment approach that balances the generalization ability of the LLM and the domain expertise of the old CL model.
no code implementations • 20 Feb 2024 • Kexin Chen, Hanqun Cao, Junyou Li, Yuyang Du, Menghao Guo, Xin Zeng, Lanqing Li, Jiezhong Qiu, Pheng Ann Heng, Guangyong Chen
The proposed approach marks a significant advancement in automating chemical literature extraction and demonstrates the potential for AI to revolutionize data management and utilization in chemistry.
no code implementations • 22 Jan 2024 • Hao Chen, Jiaze Wang, Ziyu Guo, Jinpeng Li, Donghao Zhou, Bian Wu, Chenyong Guan, Guangyong Chen, Pheng-Ann Heng
Sign language recognition (SLR) plays a vital role in facilitating communication for the hearing-impaired community.
no code implementations • 16 Nov 2023 • Kexin Chen, Junyou Li, Kunyi Wang, Yuyang Du, Jiahui Yu, Jiamin Lu, Lanqing Li, Jiezhong Qiu, Jianzhang Pan, Yi Huang, Qun Fang, Pheng Ann Heng, Guangyong Chen
Recent AI research plots a promising future of automatic chemical reactions within the chemistry society.
no code implementations • 23 Aug 2023 • Donghao Zhou, Jialin Li, Jinpeng Li, Jiancheng Huang, Qiang Nie, Yong liu, Bin-Bin Gao, Qiong Wang, Pheng-Ann Heng, Guangyong Chen
Large-scale well-annotated datasets are of great importance for training an effective object detector.
no code implementations • 4 Aug 2023 • Haotian Zhang, Huifeng Zhao, Xujun Zhang, Qun Su, Hongyan Du, Chao Shen, Zhe Wang, Dan Li, Peichen Pan, Guangyong Chen, Yu Kang, Chang-Yu Hsieh, Tingjun Hou
Drug discovery is a highly complicated process, and it is unfeasible to fully commit it to the recently developed molecular generation methods.
1 code implementation • 26 Jun 2023 • Luozhou Wang, Guibao Shen, Wenhang Ge, Guangyong Chen, Yijun Li, Ying-Cong Chen
The ``Decompose'' phase separates conditions based on pair relationships, computing the result individually for each pair.
1 code implementation • 22 Jun 2023 • Tianyue Wang, Xujun Zhang, Odin Zhang, Peichen Pan, Guangyong Chen, Yu Kang, Chang-Yu Hsieh, Tingjun Hou
Protein loop modeling is the most challenging yet highly non-trivial task in protein structure prediction.
1 code implementation • 21 Mar 2023 • Yang Yu, Danruo Deng, Furui Liu, Yueming Jin, Qi Dou, Guangyong Chen, Pheng-Ann Heng
Open-set semi-supervised learning (Open-set SSL) considers a more practical scenario, where unlabeled data and test data contain new categories (outliers) not observed in labeled data (inliers).
no code implementations • 13 Mar 2023 • Junde Xu, Zikai Lin, Donghao Zhou, Yaodong Yang, Xiangyun Liao, Bian Wu, Guangyong Chen, Pheng-Ann Heng
In particular, we evaluate our method on two representative MIM frameworks, MAE and iBOT.
no code implementations • ICCV 2023 • Hao Chen, Jiaze Wang, Kun Shao, Furui Liu, Jianye Hao, Chenyong Guan, Guangyong Chen, Pheng-Ann Heng
Specifically, our Traj-MAE employs diverse masking strategies to pre-train the trajectory encoder and map encoder, allowing for the capture of social and temporal information among agents while leveraging the effect of environment from multiple granularities.
no code implementations • 12 Mar 2023 • Yi Wang, Jiaze Wang, Jinpeng Li, Zixu Zhao, Guangyong Chen, Anfeng Liu, Pheng-Ann Heng
With Point-MAE as our baseline, our model surpasses previous methods by a significant margin, achieving 86. 3% accuracy on ScanObjectNN and 94. 1% accuracy on ModelNet40.
no code implementations • 6 Mar 2023 • Bowen Wang, Chen Liang, Jiaze Wang, Furui Liu, Shaogang Hao, Dong Li, Jianye Hao, Guangyong Chen, Xiaolong Zou, Pheng-Ann Heng
Reversely, the model Reconstructs a more robust equilibrium state prediction by transforming edge-level predictions to node-level with a sphere-fitting algorithm.
Initial Structure to Relaxed Energy (IS2RE), Direct Property Prediction
1 code implementation • 3 Mar 2023 • Danruo Deng, Guangyong Chen, Yang Yu, Furui Liu, Pheng-Ann Heng
To address this problem, we propose a novel method, Fisher Information-based Evidential Deep Learning ($\mathcal{I}$-EDL).
1 code implementation • CVPR 2023 • Donghao Zhou, Chunbin Gu, Junde Xu, Furui Liu, Qiong Wang, Guangyong Chen, Pheng-Ann Heng
In biological research, fluorescence staining is a key technique to reveal the locations and morphology of subcellular structures.
1 code implementation • 7 Dec 2022 • Zhongwei Wan, Yichun Yin, Wei zhang, Jiaxin Shi, Lifeng Shang, Guangyong Chen, Xin Jiang, Qun Liu
Recently, domain-specific PLMs have been proposed to boost the task performance of specific domains (e. g., biomedical and computer science) by continuing to pre-train general PLMs with domain-specific corpora.
1 code implementation • 23 Sep 2022 • Zhongwei Wan, Xin Liu, Benyou Wang, Jiezhong Qiu, Boyu Li, Ting Guo, Guangyong Chen, Yang Wang
The idea is to supplement the GNN-based main supervised recommendation task with the temporal representation via an auxiliary cross-view contrastive learning mechanism.
no code implementations • 15 Sep 2022 • Chen Liang, Bowen Wang, Shaogang Hao, Guangyong Chen, Pheng-Ann Heng, Xiaolong Zou
Graph neural networks (GNNs) have drawn more and more attention from material scientists and demonstrated a high capacity to establish connections between the structure and properties.
1 code implementation • 6 Sep 2022 • Hanqun Cao, Cheng Tan, Zhangyang Gao, Yilun Xu, Guangyong Chen, Pheng-Ann Heng, Stan Z. Li
Deep generative models are a prominent approach for data generation, and have been used to produce high quality samples in various domains.
no code implementations • 22 Aug 2022 • Kexin Chen, Guangyong Chen, Junyou Li, Yuansheng Huang, Pheng-Ann Heng
In high-throughput experimentation (HTE) datasets, the average yield of our methodology's top 10 high-yield reactions is relatively close to the results of ideal yield selection.
no code implementations • 20 Jul 2022 • Yang Yu, Zixu Zhao, Yueming Jin, Guangyong Chen, Qi Dou, Pheng-Ann Heng
Concretely, for trusty representation learning, we propose to incorporate pseudo labels to instruct the pair selection, obtaining more reliable representation pairs for pixel contrast.
1 code implementation • Findings (NAACL) 2022 • Yong Cao, Wei Li, Xianzhi Li, Min Chen, Guangyong Chen, Long Hu, Zhengdao Li, Hwang Kai
Sign language recognition and translation first uses a recognition module to generate glosses from sign language videos and then employs a translation module to translate glosses into spoken sentences.
1 code implementation • 30 Mar 2022 • Donghao Zhou, Pengfei Chen, Qiong Wang, Guangyong Chen, Pheng-Ann Heng
Due to the difficulty of collecting exhaustive multi-label annotations, multi-label datasets often contain partial labels.
no code implementations • 24 Mar 2022 • Bowen Wang, Guibao Shen, Dong Li, Jianye Hao, Wulong Liu, Yu Huang, HongZhong Wu, Yibo Lin, Guangyong Chen, Pheng Ann Heng
Precise congestion prediction from a placement solution plays a crucial role in circuit placement.
1 code implementation • NeurIPS 2021 • Danruo Deng, Guangyong Chen, Jianye Hao, Qiong Wang, Pheng-Ann Heng
The backpropagation networks are notably susceptible to catastrophic forgetting, where networks tend to forget previously learned skills upon learning new ones.
1 code implementation • Chemical Engineering Journal 2021 • Xiaorui Wang, Yuquan Li, Jiezhong Qiu, Guangyong Chen, Huanxiang Liu, Benben Liao, Chang-Yu Hsieh, Xiaojun Yaoa
RetroPrime achieves the Top-1 accuracy of 64. 8% and 51. 4%, when the reaction type is known and unknown, respectively, in the USPTO-50 K dataset.
Ranked #13 on Single-step retrosynthesis on USPTO-50k
no code implementations • 25 Jun 2021 • Weiwen Liu, Feng Liu, Ruiming Tang, Ben Liao, Guangyong Chen, Pheng Ann Heng
Fairness in recommendation has attracted increasing attention due to bias and discrimination possibly caused by traditional recommenders.
1 code implementation • 3 Mar 2021 • Hongyao Tang, Jianye Hao, Guangyong Chen, Pengfei Chen, Chen Chen, Yaodong Yang, Luo Zhang, Wulong Liu, Zhaopeng Meng
Value function is the central notion of Reinforcement Learning (RL).
no code implementations • ICLR 2021 • Pengfei Chen, Guangyong Chen, Junjie Ye, Jingwei Zhao, Pheng-Ann Heng
The noise in stochastic gradient descent (SGD) provides a crucial implicit regularization effect, previously studied in optimization by analyzing the dynamics of parameter updates.
1 code implementation • 10 Dec 2020 • Pengfei Chen, Junjie Ye, Guangyong Chen, Jingwei Zhao, Pheng-Ann Heng
In this work, we present a theoretical hypothesis testing and prove that noise in real-world dataset is unlikely to be CCN, which confirms that label noise should depend on the instance and justifies the urgent need to go beyond the CCN assumption. The theoretical results motivate us to study the more general and practical-relevant instance-dependent noise (IDN).
Ranked #45 on Image Classification on Clothing1M
1 code implementation • 8 Dec 2020 • Pengfei Chen, Junjie Ye, Guangyong Chen, Jingwei Zhao, Pheng-Ann Heng
For validation, we prove that a noisy validation set is reliable, addressing the critical demand of model selection in scenarios like hyperparameter-tuning and early stopping.
1 code implementation • 16 Mar 2020 • Xianzhi Li, Ruihui Li, Guangyong Chen, Chi-Wing Fu, Daniel Cohen-Or, Pheng-Ann Heng
Recently, many deep neural networks were designed to process 3D point clouds, but a common drawback is that rotation invariance is not ensured, leading to poor generalization to arbitrary orientations.
no code implementations • 25 Sep 2019 • Yujun Shi, Benben Liao, Guangyong Chen, Yun Liu, Ming-Ming Cheng, Jiashi Feng
Then, we show by experiments that DNNs under standard training rely heavily on optimizing the non-robust component in achieving decent performance.
no code implementations • 10 Sep 2019 • Yitong Meng, Xinyan Dai, Xiao Yan, James Cheng, Weiwen Liu, Benben Liao, Jun Guo, Guangyong Chen
Collaborative filtering, a widely-used recommendation technique, predicts a user's preference by aggregating the ratings from similar users.
no code implementations • 10 Sep 2019 • Yitong Meng, Guangyong Chen, Benben Liao, Jun Guo, Weiwen Liu
We further adopt the idea of CF and propose Wasserstein CF (WCF) to improve the recommendation performance on cold-start items.
no code implementations • 21 Jul 2019 • Yi Ma, Jianye Hao, Yaodong Yang, Han Li, Junqi Jin, Guangyong Chen
Our approach can work directly on directed graph data in semi-supervised nodes classification tasks.
1 code implementation • 22 Jun 2019 • Guangyong Chen, Pengfei Chen, Chang-Yu Hsieh, Chee-Kong Lee, Benben Liao, Renjie Liao, Weiwen Liu, Jiezhong Qiu, Qiming Sun, Jie Tang, Richard Zemel, Shengyu Zhang
We introduce a new molecular dataset, named Alchemy, for developing machine learning models useful in chemistry and material science.
no code implementations • 13 Jun 2019 • Pengfei Chen, Weiwen Liu, Chang-Yu Hsieh, Guangyong Chen, Shengyu Zhang
The IGNN model is based on an elegant and fundamental idea in information theory as explained in the main text, and it could be easily generalized beyond the contexts of molecular graphs considered in this work.
no code implementations • 13 Jun 2019 • Pengfei Chen, Benben Liao, Guangyong Chen, Shengyu Zhang
Most recent efforts have been devoted to defending noisy labels by discarding noisy samples from the training set or assigning weights to training samples, where the weight associated with a noisy sample is expected to be small.
no code implementations • 6 Jun 2019 • Yujun Shi, Benben Liao, Guangyong Chen, Yun Liu, Ming-Ming Cheng, Jiashi Feng
Despite many previous works studying the reason behind such adversarial behavior, the relationship between the generalization performance and adversarial behavior of DNNs is still little understood.
no code implementations • 27 May 2019 • Hongyao Tang, Jianye Hao, Guangyong Chen, Pengfei Chen, Zhaopeng Meng, Yaodong Yang, Li Wang
Value functions are crucial for model-free Reinforcement Learning (RL) to obtain a policy implicitly or guide the policy updates.
1 code implementation • 15 May 2019 • Guangyong Chen, Pengfei Chen, Yujun Shi, Chang-Yu Hsieh, Benben Liao, Shengyu Zhang
Our work is based on an excellent idea that whitening the inputs of neural networks can achieve a fast convergence speed.
3 code implementations • 13 May 2019 • Pengfei Chen, Benben Liao, Guangyong Chen, Shengyu Zhang
Noisy labels are ubiquitous in real-world datasets, which poses a challenge for robustly training deep neural networks (DNNs) as DNNs usually have the high capacity to memorize the noisy labels.
Ranked #37 on Image Classification on mini WebVision 1.0
no code implementations • 27 Sep 2018 • Pengfei Chen, Guangyong Chen, Shengyu Zhang
In Variational Auto-Encoder (VAE), the default choice of reconstruction loss function between the decoded sample and the input is the squared $L_2$.
no code implementations • ICCV 2017 • Di Lin, Guangyong Chen, Daniel Cohen-Or, Pheng-Ann Heng, Hui Huang
Our approach is to use the available depth to split the image into layers with common visual characteristic of objects/scenes, or common "scene-resolution".
Ranked #72 on Semantic Segmentation on NYU Depth v2
no code implementations • ICML 2017 • Guangyong Chen, Shengyu Zhang, Di Lin, Hui Huang, Pheng Ann Heng
While crowdsourcing has been a cost and time efficient method to label massive samples, one critical issue is quality control, for which the key challenge is to infer the ground truth from noisy or even adversarial data by various users.
no code implementations • CVPR 2016 • Fengyuan Zhu, Guangyong Chen, Pheng-Ann Heng
This paper addresses this problem and proposes a novel blind image denoising algorithm which can cope with real-world noisy images even when the noise model is not provided.
no code implementations • 13 Jan 2016 • Guangyong Chen, Fengyuan Zhu, Pheng Ann Heng
We further develop a novel online learning approach for Variational inference and use it for the online learning of HeMF, which can efficiently cope with the important large-scale DDP problem.
no code implementations • 13 Jan 2016 • Fengyuan Zhu, Guangyong Chen, Jianye Hao, Pheng-Ann Heng
This paper addresses this problem and proposes a novel blind image denoising algorithm to recover the clean image from noisy one with the unknown noise model.
no code implementations • ICCV 2015 • Guangyong Chen, Fengyuan Zhu, Pheng Ann Heng
In this paper, we address the problem of estimating noise level from a single image contaminated by additive zero-mean Gaussian noise.