Guaranteed Quantization Error Computation for Neural Network Model Compression. - Wesley Cooke; Zihao Mo; Weiming Xiang 001 (ICIT, 2023)

A Data-Driven Hybrid Automaton Framework to Modeling Complex Dynamical Systems. - Yejiang Yang; Zihao Mo; Weiming Xiang 001 (ICIT, 2023)

D3NN: Data-Driven Dual-level Neural Network Tool for Dynamical System Modeling and Abstraction. - Yejiang Yang; Zihao Mo; Weiming Xiang 001 (ADHS, 2024)

Compression Repair for Feedforward Neural Networks Based on Model Equivalence Evaluation. - Zihao Mo; Yejiang Yang; Shuaizheng Lu; Weiming Xiang 001 (ACC, 2024)

A Transition System Abstraction Framework for Neural Network Dynamical System Models. - Yejiang Yang; Zihao Mo; Hoang-Dung Tran; Weiming Xiang 001 (ACC, 2024)

Approximate Bisimulation Relation Restoration for Neural Networks Based On Knowledge Distillation. - Jie Chen; Zihao Mo; Tao Wang 023; Weiming Xiang 001 (ICMLA, 2024)

Discrepancy-Based Knowledge Distillation for Image Classification Restoration. - Zihao Mo; Yejiang Yang; Weiming Xiang 001 (ICMLA, 2024)

Efficient Neural Hybrid System Learning and Transition System Abstraction for Dynamical Systems. - Yejiang Yang; Zihao Mo; Weiming Xiang 001 (CoRR, 2024)

Observer-based safety monitoring of nonlinear dynamical systems with neural networks via quadratic constraint approach. - Tao Wang 023; Yapeng Li; Zihao Mo; Wesley Cooke; Weiming Xiang 001 (Int. J. Control, 2024)

Maximum output discrepancy computation for convolutional neural network compression. - Zihao Mo; Weiming Xiang 001 (Inf. Sci., 2024)