Hao Lan

Internet Res., 2024

Debiasing Graph Representation Learning based on Information Bottleneck.

[BibT_eX]

[DOI]

CoRR, 2024

Maize tassel detection with CA-YOLO for UAV images in complex field environments.

[BibT_eX]

[DOI]

Comput. Electron. Agric., 2024

An Interpretable Fault Diagnosis Framework based on Capsule Network with Statistical Features.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2024

2023

Transfer Function Interpolation and Extrapolation: A fast AC analysis method for evolutionary circuit design.

[BibT_eX]

[DOI]

Jingsong He

Inf. Sci., December, 2023

WavCapsNet: An Interpretable Intelligent Compound Fault Diagnosis Method by Backward Tracking.

[BibT_eX]

[DOI]

IEEE Trans. Instrum. Meas., 2023

Spatial-temporal gated graph convolutional network: a new deep learning framework for long-term traffic speed forecasting.

[BibT_eX]

[DOI]

J. Intell. Fuzzy Syst., 2023

Be Careful with PyPI Packages: You May Unconsciously Spread Backdoor Model Weights.

[BibT_eX]

[DOI]

Tianhang Zheng

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

A Fault Injection and Formal Verification Framework Based on UML Sequence Diagrams.

[BibT_eX]

[DOI]

Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering, ISSRE 2023, 2023

2022

Crucial States Estimation in Radio Block Center Handover Using Petri Nets With Unobservable Transitions.

[BibT_eX]

[DOI]

Carla Seatzu

IEEE Trans Autom. Sci. Eng., 2022

OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2022

Verification of K-step and infinite-step opacity of bounded labeled Petri nets.

[BibT_eX]

[DOI]

Carla Seatzu

Autom., 2022

Increasing-Dimension Evolution: Make the evolutionary design of passive filters more efficient.

[BibT_eX]

[DOI]

Jingsong He

Appl. Soft Comput., 2022

MHDML: Construction of a Medical Lakehouse for Multi-source Heterogeneous Data.

[BibT_eX]

[DOI]

Proceedings of the Health Information Science - 11th International Conference, 2022

OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

EAGLE: Expedited Device Placement with Automatic Grouping for Large Models.

[BibT_eX]

[DOI]

Li Chen

Proceedings of the 35th IEEE International Parallel and Distributed Processing Symposium, 2021

Accelerated Device Placement Optimization with Contrastive Learning.

[BibT_eX]

[DOI]

Li Chen

Proceedings of the ICPP 2021: 50th International Conference on Parallel Processing, Lemont, IL, USA, August 9, 2021

Generative Causal Explanations for Graph Neural Networks.

[BibT_eX]

[DOI]

Wanyu Lin

Proceedings of the 38th International Conference on Machine Learning, 2021

Intelligent Visualization System for Big Multi-source Medical Data Based on Data Lake.

[BibT_eX]

[DOI]

Proceedings of the Web Information Systems and Applications, 2021

2020

RSS: a relay-based schedule scheme for optical data center network.

[BibT_eX]

[DOI]

Photonic Netw. Commun., 2020

Verification of C-detectability using Petri nets.

[BibT_eX]

[DOI]

Inf. Sci., 2020

Initial-State Estimation of Multi-Channel Networked Discrete Event Systems.

[BibT_eX]

[DOI]

Yue Yao

IEEE Control. Syst. Lett., 2020

Comments on "A new approach for the verification of infinite-step and K-step opacity using two-way observers" [Automatica 80 (2017) 162-171].

[BibT_eX]

[DOI]

Autom., 2020

2019

Verification of infinite-step and K-step opacity Using Petri Nets.

[BibT_eX]

[DOI]

CoRR, 2019

Verification of Detectability Using Petri Nets and Detector.

[BibT_eX]

[DOI]

CoRR, 2019

Verification of Detectability in Petri Nets Using Verifier Nets.

[BibT_eX]

[DOI]

CoRR, 2019

Current-State Opacity Verification in Modular Discrete Event Systems.

[BibT_eX]

[DOI]

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Verification of Detectability in Labeled Petri Nets.

[BibT_eX]

[DOI]