Ye Yuan

Orcid: 0000-0001-7858-0437

Affiliations:
  • Huazhong University of Science and Technology, School of Automation, Wuhan, China
  • University of California Berkeley, CA, USA (former)
  • University of Cambridge, Department of Engineering, UK (PhD 2012)


According to our database1, Ye Yuan authored at least 107 papers between 2009 and 2024.

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Bibliography

2024
A Sampling Theorem for Exact Identification of Continuous-Time Nonlinear Dynamical Systems.
IEEE Trans. Autom. Control., December, 2024

Online Learning Based Shape Control for a Soft Manipulator Based on Spatial Features Feedback.
IEEE Robotics Autom. Lett., November, 2024

Switched Momentum Dynamics Identification for Robot Collision Detection.
IEEE Trans. Ind. Informatics, September, 2024

Data-Driven Koopman Learning and Prediction of Piezoelectric Tube Scanner Hysteresis.
IEEE Trans. Syst. Man Cybern. Syst., June, 2024

A Transfer Learning-Based Method for Personalized State of Health Estimation of Lithium-Ion Batteries.
IEEE Trans. Neural Networks Learn. Syst., January, 2024

A Generalized Nyquist-Shannon Sampling Theorem Using the Koopman Operator.
IEEE Trans. Signal Process., 2024

Active Learning-Aided Design of a Flexible Tactile Sensor Array for Recognizing Properties of Deformable Objects.
IEEE Trans. Instrum. Meas., 2024

Early warning of atrial fibrillation using deep learning.
Patterns, 2024

An Iterative Min-Min Optimization Method for Sparse Bayesian Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Deep probabilistic graphical modeling for robust multivariate time series anomaly detection with missing data.
Reliab. Eng. Syst. Saf., October, 2023

BoostTree and BoostForest for Ensemble Learning.
IEEE Trans. Pattern Anal. Mach. Intell., July, 2023

Intelligent Fault Diagnosis With Noisy Labels via Semisupervised Learning on Industrial Time Series.
IEEE Trans. Ind. Informatics, June, 2023

Noise-Aware Sparse Gaussian Processes and Application to Reliable Industrial Machinery Health Monitoring.
IEEE Trans. Ind. Informatics, April, 2023

Inverse Power Flow Problem.
IEEE Trans. Control. Netw. Syst., March, 2023

A two-stage integrated method for early prediction of remaining useful life of lithium-ion batteries.
Knowl. Based Syst., 2023

Estimating the State of Health for Lithium-ion Batteries: A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach.
IEEE CAA J. Autom. Sinica, 2023

A Generalized Nyquist-Shannon Sampling Theorem Using the Koopman Operator.
CoRR, 2023

Boolean Internal Structure Reconstruction from Collapsed Small-Scale Networks.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
Homecare-Oriented ECG Diagnosis With Large-Scale Deep Neural Network for Continuous Monitoring on Embedded Devices.
IEEE Trans. Instrum. Meas., 2022

Data-Driven Discovery of Block-Oriented Nonlinear Models Using Sparse Null-Subspace Methods.
IEEE Trans. Cybern., 2022

Design of a Soft Gripper With Improved Microfluidic Tactile Sensors for Classification of Deformable Objects.
IEEE Robotics Autom. Lett., 2022

A Piecewise Learning Framework for Control of Unknown Nonlinear Systems with Stability Guarantees.
Proceedings of the Learning for Dynamics and Control Conference, 2022

Sen-Glove: A Lightweight Wearable Glove for Hand Assistance with Soft Joint Sensing.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

On Almost Sure Convergence Rates of Stochastic Gradient Methods.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
Modeling and Control of Swing Oscillation of Underactuated Indoor Miniature Autonomous Blimps.
Unmanned Syst., 2021

System Aliasing in Dynamic Network Reconstruction: Issues on Low Sampling Frequencies.
IEEE Trans. Autom. Control., 2021

A Full Bayesian Approach to Sparse Network Inference Using Heterogeneous Datasets.
IEEE Trans. Autom. Control., 2021

Reply to: Clinical interpretation of an interpretable prognostic model for patients with COVID-19.
Nat. Mach. Intell., 2021

Reply to: Consider the laboratory aspects in developing patient prediction models.
Nat. Mach. Intell., 2021

Li Yan et al. reply.
Nat. Mach. Intell., 2021

DeFed: A Principled Decentralized and Privacy-Preserving Federated Learning Algorithm.
CoRR, 2021

Manipulability and Robustness Optimization of the Cable-Driven Redundant Soft Manipulator.
Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2021

2020
Bayesian Learning-Based Harmonic State Estimation in Distribution Systems With Smart Meter and DPMU Data.
IEEE Trans. Smart Grid, 2020

A Fast Optimal Power Flow Algorithm Using Powerball Method.
IEEE Trans. Ind. Informatics, 2020

Optimize TSK Fuzzy Systems for Regression Problems: Minibatch Gradient Descent With Regularization, DropRule, and AdaBound (MBGD-RDA).
IEEE Trans. Fuzzy Syst., 2020

An interpretable mortality prediction model for COVID-19 patients.
Nat. Mach. Intell., 2020

Principled reward shaping for reinforcement learning via lyapunov stability theory.
Neurocomputing, 2020

Wasserstein distance based deep adversarial transfer learning for intelligent fault diagnosis with unlabeled or insufficient labeled data.
Neurocomputing, 2020

BoostTree and BoostForest for Ensemble Learning.
CoRR, 2020

A Hessian-Free Gradient Flow (HFGF) method for the optimisation of deep learning neural networks.
Comput. Chem. Eng., 2020

High precision variational Bayesian inference of sparse linear networks.
Autom., 2020

pbSGD: Powered Stochastic Gradient Descent Methods for Accelerated Non-Convex Optimization.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

State of health estimation for lithium-ion batteries with dynamic time warping and deep kernel learning model.
Proceedings of the 18th European Control Conference, 2020

2019
On Identification of Distribution Grids.
IEEE Trans. Control. Netw. Syst., 2019

Dynamical differential expression (DyDE) reveals the period control mechanisms of the Arabidopsis circadian oscillator.
PLoS Comput. Biol., 2019

On the Powerball Method: Variants of Descent Methods for Accelerated Optimization.
IEEE Control. Syst. Lett., 2019

Machine Discovery of Partial Differential Equations from Spatiotemporal Data.
CoRR, 2019

A Novel GAN-based Fault Diagnosis Approach for Imbalanced Industrial Time Series.
CoRR, 2019

Optimize TSK Fuzzy Systems for Big Data Regression Problems: Mini-Batch Gradient Descent with Regularization, DropRule and AdaBound (MBGD-RDA).
CoRR, 2019

Wasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis.
CoRR, 2019

Artificial Intelligent Diagnosis and Monitoring in Manufacturing.
CoRR, 2019

Blind identification of fully observed linear time-varying systems via sparse recovery.
Autom., 2019

A survey of distributed optimization.
Annu. Rev. Control., 2019

Special section on control of complex networked systems (CCNS): Recent results and future trends.
Annu. Rev. Control., 2019

Deep Grasping Prediction with Antipodal Loss for Dual Arm Manipulators.
Proceedings of the Intelligent Robotics and Applications - 12th International Conference, 2019

2018
Identification of Nonlinear State-Space Systems From Heterogeneous Datasets.
IEEE Trans. Control. Netw. Syst., 2018

Online Bearing Remaining Useful Life Prediction Based on a Novel Degradation Indicator and Convolutional Neural Networks.
CoRR, 2018

Data-driven Discovery of Cyber-Physical Systems.
CoRR, 2018

Global Network Prediction from Local Node Dynamics.
CoRR, 2018

Sparse Bayesian Harmonic State Estimation.
Proceedings of the 2018 IEEE International Conference on Communications, 2018

Sparse Bayesian Learning-Based Adaptive Impedance Control in Physical Human-Robot Interaction.
Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2018

Distributed Hunting for Multi USVs Based on Cyclic Estimation and Pursuit.
Proceedings of the Intelligent Robotics and Applications - 11th International Conference, 2018

Distributed Finite-Time Optimization.
Proceedings of the 14th IEEE International Conference on Control and Automation, 2018

Learning-based Adaptive Robust Control of Manipulated Pneumatic Artificial Muscle Driven by H2-based Metal Hydride.
Proceedings of the 14th IEEE International Conference on Automation Science and Engineering, 2018

2017
Electrospinning Sedimentary Microstructure Feedback Control by Tuning Substrate Linear Machine Velocity.
IEEE Trans. Ind. Electron., 2017

A Minimal Realization Technique for the Dynamical Structure Function of a Class of LTI Systems.
IEEE Trans. Control. Netw. Syst., 2017

Network Identifiability from Intrinsic Noise.
IEEE Trans. Autom. Control., 2017

Blind Identification of Fully Observed Discrete-Time Linear Time-Varying Systems via Sparse Recovery.
CoRR, 2017

Distributed Kalman filtering with minimum-time consensus algorithm.
CoRR, 2017

Identification of nonlinear sparse networks using sparse Bayesian learning.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2016
A Sparse Bayesian Approach to the Identification of Nonlinear State-Space Systems.
IEEE Trans. Autom. Control., 2016

On the Powerball Method.
CoRR, 2016

On Identification of Sparse Multivariable ARX Model: A Sparse Bayesian Learning Approach.
CoRR, 2016

On Identification of Dynamical Structure Functions: A Sparse Bayesian Learning Approach.
CoRR, 2016

Event Detection and Localization in Distribution Grids with Phasor Measurement Units.
CoRR, 2016

2015
Distributed Finite-Time Average Consensus in Digraphs in the Presence of Time Delays.
IEEE Trans. Control. Netw. Syst., 2015

On minimal realisations of dynamical structure functions.
Autom., 2015

Online fault diagnosis for nonlinear power systems.
Autom., 2015

Dynamical Structure Function and Granger Causality: Similarities and differences.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

Identifying biochemical reaction networks from heterogeneous datasets.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

A stochastic framework for the design of transient and steady state behavior of biochemical reaction networks.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2014
On minimal realisations of dynamical structure functions.
CoRR, 2014

Finite-time road grade computation for a vehicle platoon.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

H2 norm based network volatility measures.
Proceedings of the American Control Conference, 2014

Network reconstruction from intrinsic noise: Minimum-phase systems.
Proceedings of the American Control Conference, 2014

2013
How Can Online Schedules Improve Communication and Estimation Tradeoff?
IEEE Trans. Signal Process., 2013

Finite Horizon LQR Control With Limited Controller-System Communication.
IEEE Trans. Autom. Control., 2013

Network Reconstruction from Intrinsic Noise.
CoRR, 2013

Decentralised minimum-time consensus.
Autom., 2013

Network reconstruction using knock-out and over-expression data.
Proceedings of the 12th European Control Conference, 2013

Distributed Kalman Filter with minimum-time covariance computation.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Real-time fault diagnosis for large-scale nonlinear power networks.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Decentralised minimum-time average consensus in digraphs.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

2012
Minimal realization of the dynamical structure function and its application to network reconstruction
CoRR, 2012

Reconstruction of Arbitrary Biochemical Reaction Networks: A Compressive Sensing Approach
CoRR, 2012

Quantifying crosstalk in biochemical systems.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

Reconstruction of arbitrary biochemical reaction networks: A compressive sensing approach.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

Robust network reconstruction in polynomial time.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

Dynamical structure function identifiability conditions enabling signal structure reconstruction.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

Decentralised minimal-time dynamic consensus.
Proceedings of the American Control Conference, 2012

Sensor data scheduling for linear quadratic Gaussian control with full state feedback.
Proceedings of the American Control Conference, 2012

2011
Robust dynamical network structure reconstruction.
Autom., 2011

Decentralised minimal-time consensus.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2010
Robust dynamical network reconstruction.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

Minimal-time network reconstruction for DTLTI systems.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

2009
Minimal dynamical structure realisations with application to network reconstruction from data.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009

Decentralised final value theorem for discrete-time LTI systems with application to minimal-time distributed consensus.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009


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