Duxin Chen
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View article: The Robustness of Differentiable Causal Discovery in Misspecified Scenarios
The Robustness of Differentiable Causal Discovery in Misspecified Scenarios Open
Causal discovery aims to learn causal relationships between variables from targeted data, making it a fundamental task in machine learning. However, causal discovery algorithms often rely on unverifiable causal assumptions, which are usual…
View article: A stretchable liquid metal switch for interactive and autonomous soft machines
A stretchable liquid metal switch for interactive and autonomous soft machines Open
Soft machines harness material-level physical intelligence to perform adaptive tasks, enabling advancements in biomedical and human-machine interaction fields. Soft switches are the basic building blocks to achieve intelligent functions li…
View article: Decoupling Spatio-Temporal Prediction: When Lightweight Large Models Meet Adaptive Hypergraphs
Decoupling Spatio-Temporal Prediction: When Lightweight Large Models Meet Adaptive Hypergraphs Open
Spatio-temporal prediction is a pivotal task with broad applications in traffic management, climate monitoring, energy scheduling, etc. However, existing methodologies often struggle to balance model expressiveness and computational effici…
View article: Critical nodes identification in complex networks: a survey
Critical nodes identification in complex networks: a survey Open
Complex networks have become essential tools for understanding diverse phenomena in social systems, traffic systems, biomolecular systems, and financial systems. Identifying critical nodes is a central theme in contemporary research, servi…
View article: Pattern phase transition of spin particle lattice system
Pattern phase transition of spin particle lattice system Open
To better understand the pattern phase transition of both physical and biological systems, we investigate a two-dimensional spin particle lattice system using statistical mechanics methods together with XY model governed by Hamiltonian equ…
View article: Investigating Hypernode Classification of Complex Systems Based on High-order Graph Neural Networks
Investigating Hypernode Classification of Complex Systems Based on High-order Graph Neural Networks Open
Investigating latent interactions beyond direct connections is essential for analyzing complex networks. However, traditional graph structures often fail to capture complex relationships, especially in the high-order interactions among mul…
View article: Spatio-Temporal Graphical Counterfactuals: An Overview
Spatio-Temporal Graphical Counterfactuals: An Overview Open
Counterfactual thinking is a critical yet challenging topic for artificial intelligence to learn knowledge from data and ultimately improve their performances for new scenarios. Many research works, including Potential Outcome Model and St…
View article: Cross-modal missing time-series imputation using dense spatio-temporal transformer nets
Cross-modal missing time-series imputation using dense spatio-temporal transformer nets Open
Due to irregular sampling or device failure, the data collected from sensor network has missing value, that is, missing time-series data occurs. To address this issue, many methods have been proposed to impute random or non-random missing …
View article: Improving traffic time‐series predictability by imputing continuous non‐random missing data
Improving traffic time‐series predictability by imputing continuous non‐random missing data Open
Continuous non‐random data missing can be a challenging task for model prediction in intelligent transport system (ITS). In ITS, many methods have been proposed to solve this problem. However, the imputation accuracy of them is far from ac…
View article: Identifying vital nodes in recovering dynamical process of networked system
Identifying vital nodes in recovering dynamical process of networked system Open
Vital nodes identification is the problem of identifying the most significant nodes in complex networks, which is crucial in understanding the property of the networks and has applications in various fields such as pandemic controlling and…
View article: Interpretable System Identification and Long-term Prediction on Time-Series Data
Interpretable System Identification and Long-term Prediction on Time-Series Data Open
Time-series prediction has drawn considerable attention during the past decades fueled by the emerging advances of deep learning methods. However, most neural network based methods lack interpretability and fail in extracting the hidden me…
View article: Identifying Unique Spatial-Temporal Bayesian Network without Markov Equivalence
Identifying Unique Spatial-Temporal Bayesian Network without Markov Equivalence Open
Identifying vanilla Bayesian network to model spatial-temporal causality can be a critical yet challenging task. Different Markovian-equivalent directed acyclic graphs would be identified if the identifiability is not satisfied. To address…
View article: Coordinating directional switches in pigeon flocks: The role of nonlinear interactions
Coordinating directional switches in pigeon flocks: The role of nonlinear interactions Open
MatLab Code for paper "Coordinating directional switches in pigeon flocks: The role of nonlinear interactions".
View article: Coordinating directional switches in pigeon flocks: The role of nonlinear interactions
Coordinating directional switches in pigeon flocks: The role of nonlinear interactions Open
MatLab Code for paper "Coordinating directional switches in pigeon flocks: The role of nonlinear interactions".
View article: Coordinating directional switches in pigeon flocks: the role of nonlinear interactions
Coordinating directional switches in pigeon flocks: the role of nonlinear interactions Open
The mechanisms inducing unpredictably directional switches in collective and moving biological entities are largely unclear. Deeply understanding such mechanisms is beneficial to delicate design of biologically inspired devices with partic…
View article: Rotational Flocking with Spontaneous Directional Changes
Rotational Flocking with Spontaneous Directional Changes Open
Revealing the underlying decision‐making strategy governing the high‐group polarization accompanied by conflicting individual preferences may play a central part in the lives of social animals. Hereby, we construct a structured spin model …
View article: Pattern phase transitions of self-propelled particles: gases, crystals, liquids, and mills
Pattern phase transitions of self-propelled particles: gases, crystals, liquids, and mills Open
To understand the collective behaviors of biological swarms, flocks, and colonies, we investigated the non-equilibrium dynamic patterns of self-propelled particle systems using statistical mechanics methods and H-stability analysis of Hami…