PALOMA: A Process Algebra for Located Markovian Agents. - Cheng Feng 004; Jane Hillston (QEST, 2014)

Patch-based Hybrid Modelling of Spatially Distributed Systems by Using Stochastic HYPE - ZebraNet as an Example. - Cheng Feng 004 (QAPL, 2014)

Performance Analysis of Collective Adaptive Behaviour in Time and Space. - Cheng Feng 004; Marco Gribaudo; Jane Hillston (UKPEW, 2014)

Speed-Up of Stochastic Simulation of PCTMC Models by Statistical Model Reduction. - Cheng Feng 004; Jane Hillston (EPEW, 2015)

Moment-Based Probabilistic Prediction of Bike Availability for Bike-Sharing Systems. - Cheng Feng 004; Jane Hillston; Daniël Reijsbergen (QEST, 2016)

Automatic Moment-Closure Approximation of Spatially Distributed Collective Adaptive Systems. - Cheng Feng 004; Jane Hillston; Vashti Galpin (ACM Trans. Model. Comput. Simul., 2016)

Multi-level Anomaly Detection in Industrial Control Systems via Package Signatures and LSTM Networks. - Cheng Feng 004; Tingting Li 001; Deeph Chana (DSN, 2017)

A Deep Learning-based Framework for Conducting Stealthy Attacks in Industrial Control Systems. - Cheng Feng 004; Tingting Li 001; Zhanxing Zhu; Deeph Chana (CoRR, 2017)

Moment-based availability prediction for bike-sharing systems. - Cheng Feng 004; Jane Hillston; Daniël Reijsbergen (Perform. Evaluation, 2017)

Availability Modeling of Generalized k-Out-of-n: G Warm Standby Systems With PEPA. - Xiaoyue Wu; Jane Hillston; Cheng Feng 004 (IEEE Trans. Syst. Man Cybern. Syst., 2017)

Process algebra for located Markovian agents and scalable analysis techniques for the modelling of Collective Adaptive Systems. - Cheng Feng 004 (2017)

Improving ICS Cyber Resilience through Optimal Diversification of Network Resources. - Tingting Li 001; Cheng Feng 004; Chris Hankin (CoRR, 2018)

Accelerating simulation of Population Continuous Time Markov Chains via automatic model reduction. - Cheng Feng 004; Jane Hillston (Perform. Evaluation, 2018)

A Systematic Framework to Generate Invariants for Anomaly Detection in Industrial Control Systems. - Cheng Feng 004; Venkata Reddy Palleti; Aditya Mathur; Deeph Chana (NDSS, 2019)

RelSen: An Optimization-based Framework for Simultaneously Sensor Reliability Monitoring and Data Cleaning. - Cheng Feng 004; Xiao Liang; Daniel Schneegass; Pengwei Tian (CIKM, 2020)

Scalable Approach to Enhancing ICS Resilience by Network Diversity. - Tingting Li 001; Cheng Feng 004; Chris Hankin (DSN, 2020)

RelSen: An Optimization-based Framework for Simultaneous Sensor Reliability Monitoring and Process State Estimation. - Cheng Feng 004; Xiao Liang; Daniel Schneegass; Pengwei Tian (CoRR, 2020)

Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering. - Cheng Feng 004; Pengwei Tian (KDD, 2021)

Stacking VAE with Graph Neural Networks for Effective and Interpretable Time Series Anomaly Detection. - Wenkai Li; Wenbo Hu 001; Ning Chen 002; Cheng Feng 004 (CoRR, 2021)

Nonlinear Hawkes Processes in Time-Varying System. - Feng Zhou 011; Quyu Kong; Yixuan Zhang 006; Cheng Feng 004; Jun Zhu 001 (CoRR, 2021)

Robust Learning of Deep Time Series Anomaly Detection Models with Contaminated Training Data. - Wenkai Li; Cheng Feng 004; Ting Chen 006; Jun Zhu 001 (CoRR, 2022)

Efficient Inference for Dynamic Flexible Interactions of Neural Populations. - Feng Zhou 011; Quyu Kong; Zhijie Deng; Jichao Kan; Yixuan Zhang 006; Cheng Feng 004; Jun Zhu 001 (J. Mach. Learn. Res., 2022)

StackVAE-G: An efficient and interpretable model for time series anomaly detection. - Wenkai Li; Wenbo Hu 001; Ting Chen 006; Ning Chen 002; Cheng Feng 004 (AI Open, 2022)

PARs: Predicate-based Association Rules for Efficient and Accurate Anomaly Explanation. - Cheng Feng 004 (CIKM, 2024)

General Time Transformer: an Encoder-only Foundation Model for Zero-Shot Multivariate Time Series Forecasting. - Cheng Feng 004; Long Huang; Denis Krompass (CIKM, 2024)

A cGAN Ensemble-based Uncertainty-aware Surrogate Model for Offline Model-based Optimization in Industrial Control Problems. - Cheng Feng 004 (IJCNN, 2024)

Only the Curve Shape Matters: Training Foundation Models for Zero-Shot Multivariate Time Series Forecasting through Next Curve Shape Prediction. - Cheng Feng 004; Long Huang; Denis Krompass (CoRR, 2024)