1 code implementation • 11 Dec 2020 • Yuntian Chen, Dou Huang, Dongxiao Zhang, Junsheng Zeng, Nanzhe Wang, Haoran Zhang, Jinyue Yan
Machine learning models have been successfully used in many scientific and engineering fields.
1 code implementation • CVPR 2023 • Qian Li, Yuxiao Hu, Ye Liu, Dongxiao Zhang, Xin Jin, Yuntian Chen
Classical adversarial attacks for Face Recognition (FR) models typically generate discrete examples for target identity with a single state image.
1 code implementation • 30 May 2023 • Jiaxin Gao, WenBo Hu, Yuntian Chen
Long-term time series forecasting (LTSF) is a crucial aspect of modern society, playing a pivotal role in facilitating long-term planning and developing early warning systems.
2 code implementations • 9 Jun 2021 • Yuntian Chen, Yingtao Luo, Qiang Liu, Hao Xu, Dongxiao Zhang
Partial differential equations (PDEs) are concise and understandable representations of domain knowledge, which are essential for deepening our understanding of physical processes and predicting future responses.
1 code implementation • 26 Apr 2020 • Yuntian Chen, Dongxiao Zhang
In this study, we propose an ensemble long short-term memory (EnLSTM) network, which can be trained on a small dataset and process sequential data.
1 code implementation • 11 May 2022 • Mengge Du, Yuntian Chen, Dongxiao Zhang
Imposing physical constraints on neural networks as a method of knowledge embedding has achieved great progress in solving physical problems described by governing equations.
1 code implementation • 4 Oct 2022 • Mengge Du, Yuntian Chen, Dongxiao Zhang
The working mechanisms of complex natural systems tend to abide by concise and profound partial differential equations (PDEs).
Model-based Reinforcement Learning reinforcement-learning +1
1 code implementation • 30 Sep 2023 • Qinglong Cao, Zhengqin Xu, Yuntian Chen, Chao Ma, Xiaokang Yang
Existing prompt learning methods often lack domain-awareness or domain-transfer mechanisms, leading to suboptimal performance due to the misinterpretation of specific images in natural image patterns.
1 code implementation • 3 Jul 2023 • Hao Xu, Yuntian Chen, Dongxiao Zhang
Our model-agnostic framework can be applied to a variety of common network architectures, providing a comprehensive understanding of the role of prior knowledge in deep learning models.
1 code implementation • 29 May 2023 • Qinglong Cao, Yuntian Chen, Chao Ma, Xiaokang Yang
Few-shot aerial image segmentation is a challenging task that involves precisely parsing objects in query aerial images with limited annotated support.
no code implementations • 26 Apr 2020 • Yuntian Chen, Dongxiao Zhang
In the training process, the model prediction is mapped to the space of value that conforms to the physical mechanism through the projection matrix, and then the model is trained based on the indirect labels.
no code implementations • 22 Aug 2020 • Zhaocheng Liu, Qiang Liu, Haoli Zhang, Yuntian Chen
Simple classifiers, e. g., Logistic Regression (LR), are globally interpretable, but not powerful enough to model complex nonlinear interactions among features in tabular data.
no code implementations • 14 Mar 2020 • Zhongfei Xiong, Ruo-Yang Zhang, Rui Yu, C. T. Chan, Yuntian Chen
It was recently demonstrated that the connectivities of bands emerging from zero frequency in dielectric photonic crystals are distinct from their electronic counterparts with the same space groups.
Optics Mesoscale and Nanoscale Physics
no code implementations • 11 Jan 2021 • Weijin Chen, Qingdong Yang, Yuntian Chen, Wei Liu
Chiral optical effects are generally quantified along some specific incident directions of exciting waves (especially for extrinsic chiralities of achiral structures) or defined as direction-independent properties by averaging the responses among all structure orientations.
Optics
no code implementations • 17 Feb 2021 • Haofan Yang, Jing Xu, Zhongfei Xiong, Xinda Lu, Ruo-Yang Zhang, Yuntian Chen, Shuang Zhang
In optics, various photonic topological circuits have been developed, which were based on classical emulation of either quantum spin Hall effect or quantum valley Hall effect.
Optics
no code implementations • 24 Feb 2021 • Qiang Liu, Zhaocheng Liu, Haoli Zhang, Yuntian Chen, Jun Zhu
Accordingly, we can design an automatic feature crossing method to find feature interactions in DNN, and use them as cross features in LR.
no code implementations • 24 Nov 2020 • Hongkang Shi, Yuqiong Cheng, Zheng Yang, Yuntian Chen, Shubo Wang
Optical isolation enables nonreciprocal manipulations of light with broad applications in optical communications.
Optics
no code implementations • 31 May 2021 • Junsheng Zeng, Hao Xu, Yuntian Chen, Dongxiao Zhang
Although deep-learning has been successfully applied in a variety of science and engineering problems owing to its strong high-dimensional nonlinear mapping capability, it is of limited use in scientific knowledge discovery.
no code implementations • 2 Jun 2021 • Yingtao Luo, Qiang Liu, Yuntian Chen, WenBo Hu, Tian Tian, Jun Zhu
Especially, the discovery of PDEs with highly nonlinear coefficients from low-quality data remains largely under-addressed.
no code implementations • 15 Feb 2022 • Yuntian Chen, Dongxiao Zhang
Scientific research's mandate is to comprehend and explore the world, as well as to improve it based on experience and knowledge.
no code implementations • 16 Apr 2022 • Hao Xu, Yuntian Chen, Dongxiao Zhang
The interpretability of deep neural networks has attracted increasing attention in recent years, and several methods have been created to interpret the "black box" model.
no code implementations • 20 Jun 2022 • Yuntian Chen, Dongxiao Zhang, Qun Zhao, Dexun Liu
An algorithm named InterOpt for optimizing operational parameters is proposed based on interpretable machine learning, and is demonstrated via optimization of shale gas development.
no code implementations • 5 Oct 2022 • Jiaxin Gao, WenBo Hu, Dongxiao Zhang, Yuntian Chen
Accurate electrical load forecasting is beneficial for better scheduling of electricity generation and saving electrical energy.
no code implementations • 20 Nov 2022 • Qinglong Cao, Yuntian Chen, Xiwen Yao, Junwei Han
Few-shot semantic segmentation task aims at performing segmentation in query images with a few annotated support samples.
no code implementations • 27 Sep 2023 • Hao Xu, Yuntian Chen, Zhenzhong Zeng, Nina Li, Jian Li, Dongxiao Zhang
Through this AI-driven knowledge discovery, we uncover previously undisclosed explicit equations that shed light on the connection between terrain features and precipitation patterns.
no code implementations • 1 Jun 2023 • Qinglong Cao, Yuntian Chen, Chao Ma, Xiaokang Yang
Few-shot semantic segmentation (FSS) aims to segment objects of unseen classes in query images with only a few annotated support images.
no code implementations • 7 Nov 2023 • Dashan Zhang, Yuntian Chen, Shiyi Chen
However, when facing the complex real-world, most of the existing methods still strongly rely on the quantity and quality of observation data.
no code implementations • 1 Dec 2023 • Longfeng Nie, Yuntian Chen, Mengge Du, Changqi Sun, Dongxiao Zhang
Compared with widely used semantic segmentation networks, including SegNet, PSPNet, DeepLabV3+, UNet, and ResUnet, our proposed model CldNet with an accuracy of 80. 89+-2. 18% is state-of-the-art in identifying cloud types and has increased by 32%, 46%, 22%, 2%, and 39%, respectively.
no code implementations • 1 Dec 2023 • Longfeng Nie, Yuntian Chen, Dongxiao Zhang, Xinyue Liu, Wentian Yuan
Specifically, the temporal and spatial characteristics of remote sensing data of the satellite Himawari-8 are extracted and fused by recurrent neural network (RNN) and convolution operation, respectively.
no code implementations • 4 Dec 2023 • Jiaxin Gao, Qinglong Cao, Yuntian Chen
Utilizing the MoE framework, MoE-AMC seamlessly combines the strengths of LSRM (a Transformer-based model) for handling low SNR signals and HSRM (a ResNet-based model) for high SNR signals.
no code implementations • 26 Nov 2023 • Chengchun Liu, Yuntian Chen, Fanyang Mo
Organic chemistry is undergoing a major paradigm shift, moving from a labor-intensive approach to a new era dominated by automation and artificial intelligence (AI).
no code implementations • 10 Dec 2023 • Jiaxin Gao, Yuxiao Hu, Qinglong Cao, Siqi Dai, Yuntian Chen
Time series forecasting (TSF) holds significant importance in modern society, spanning numerous domains.
no code implementations • 12 Dec 2023 • Qian Li, Yuxiao Hu, Yinpeng Dong, Dongxiao Zhang, Yuntian Chen
Adversarial training is often formulated as a min-max problem, however, concentrating only on the worst adversarial examples causes alternating repetitive confusion of the model, i. e., previously defended or correctly classified samples are not defensible or accurately classifiable in subsequent adversarial training.
no code implementations • 12 Dec 2023 • Qinglong Cao, Zhengqin Xu, Yuntian Chen, Chao Ma, Xiaokang Yang
Specifically, the proposed method involves using domain-specific vision features from domain-specific foundation models to guide the transformation of generalized contextual embeddings from the language branch into a specialized space within the quaternion networks.
no code implementations • 2 Dec 2023 • Changqi Sun, Hao Xu, Yuntian Chen, Dongxiao Zhang
Explainable artificial intelligence (XAI) aims to develop transparent explanatory approaches for "black-box" deep learning models.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI)
no code implementations • 31 Dec 2023 • Yuxiao Hu, Qian Li, Xiaodan Shi, Jinyue Yan, Yuntian Chen
To address these limitations, we present a novel Multi-spatial Multi-temporal air quality forecasting method based on Graph Convolutional Networks and Gated Recurrent Units (M2G2), bridging the gap in air quality forecasting across spatial and temporal scales.
1 code implementation • 25 Jan 2024 • Siyu Lou, Chengchun Liu, Yuntian Chen, Fanyang Mo
Thin-layer chromatography (TLC) is a crucial technique in molecular polarity analysis.
no code implementations • 29 Jan 2024 • Qinglong Cao, Zhengqin Xu, Chao Ma, Xiaokang Yang, Yuntian Chen
To tackle this dilemma, we comprehensively consider the flow visual properties, including the unique flow imaging principle and morphological information, and propose the first flow visual property-informed FISR algorithm.
no code implementations • 16 Apr 2024 • Dayin Chen, Xiaodan Shi, Haoran Zhang, Xuan Song, Dongxiao Zhang, Yuntian Chen, Jinyue Yan
We believe this study has the potential to advance the practical application of phone-based ambient temperature measurement, facilitating energy-saving efforts in buildings.