Search Results for author: Qunxi Zhu

Found 10 papers, 3 papers with code

Governing equation discovery of a complex system from snapshots

no code implementations22 Oct 2024 Qunxi Zhu, Bolin Zhao, Jingdong Zhang, Peiyang Li, Wei Lin

Complex systems in physics, chemistry, and biology that evolve over time with inherent randomness are typically described by stochastic differential equations (SDEs).

Density Estimation Equation Discovery

Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation law

no code implementations4 Jun 2024 Jingdong Zhang, Qunxi Zhu, Wei Lin

Our results suggest that feeding the prior knowledge of the underlying system and the mathematical theory appropriately to the learning framework can reinforce the capability of machine learning in solving physical problems.

Switched Flow Matching: Eliminating Singularities via Switching ODEs

no code implementations19 May 2024 Qunxi Zhu, Wei Lin

Continuous-time generative models, such as Flow Matching (FM), construct probability paths to transport between one distribution and another through the simulation-free learning of the neural ordinary differential equations (ODEs).

Attribute

From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems

no code implementations19 May 2024 Xin Li, Jingdong Zhang, Qunxi Zhu, Chengli Zhao, Xue Zhang, Xiaojun Duan, Wei Lin

We then incorporate the estimated spatial gradients as additional inputs to a neural network.

Let's Rectify Step by Step: Improving Aspect-based Sentiment Analysis with Diffusion Models

1 code implementation23 Feb 2024 Shunyu Liu, Jie zhou, Qunxi Zhu, Qin Chen, Qingchun Bai, Jun Xiao, Liang He

Aspect-Based Sentiment Analysis (ABSA) stands as a crucial task in predicting the sentiment polarity associated with identified aspects within text.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1

A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition

1 code implementation21 May 2023 Limao Xiong, Jie zhou, Qunxi Zhu, Xiao Wang, Yuanbin Wu, Qi Zhang, Tao Gui, Xuanjing Huang, Jin Ma, Ying Shan

Particularly, we propose a Confidence-based Partial Label Learning (CPLL) method to integrate the prior confidence (given by annotators) and posterior confidences (learned by models) for crowd-annotated NER.

named-entity-recognition Named Entity Recognition +2

Neural Delay Differential Equations: System Reconstruction and Image Classification

no code implementations11 Apr 2023 Qunxi Zhu, Yao Guo, Wei Lin

Neural Ordinary Differential Equations (NODEs), a framework of continuous-depth neural networks, have been widely applied, showing exceptional efficacy in coping with representative datasets.

Classification Image Classification

Neural Stochastic Control

1 code implementation15 Sep 2022 Jingdong Zhang, Qunxi Zhu, Wei Lin

These two stochastic controllers thus are complementary in applications.

Neural Piecewise-Constant Delay Differential Equations

no code implementations4 Jan 2022 Qunxi Zhu, Yifei Shen, Dongsheng Li, Wei Lin

Continuous-depth neural networks, such as the Neural Ordinary Differential Equations (ODEs), have aroused a great deal of interest from the communities of machine learning and data science in recent years, which bridge the connection between deep neural networks and dynamical systems.

Neural Delay Differential Equations

no code implementations ICLR 2021 Qunxi Zhu, Yao Guo, Wei Lin

Neural Ordinary Differential Equations (NODEs), a framework of continuous-depth neural networks, have been widely applied, showing exceptional efficacy in coping with some representative datasets.

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