24 citations · 96 across the 43 of their papers we have counts for
12 papers · 1 filter
Safeguarding Learning-based Control for Smart Energy Systems with Sampling Specifications
Chih-Hong Cheng, Venkatesh Prasad Venkataramanan, Pragya Kirti Gupta +2
We study challenges using reinforcement learning in controlling energy systems, where apart from performance requirements, one has additional safety requirements such as avoiding b…
Facilitating Change Implementation for Continuous ML-Safety Assurance
Chih-Hong Cheng, Nguyen Anh Vu Doan, Balahari Balu +9
We propose a method for deploying a safety-critical machine-learning component into continuously evolving environments where an increased degree of automation in the engineering pr…
Prioritizing Corners in OoD Detectors via Symbolic String Manipulation
Chih-Hong Cheng, Changshun Wu, Emmanouil Seferis +1
For safety assurance of deep neural networks (DNNs), out-of-distribution (OoD) monitoring techniques are essential as they filter spurious input that is distant from the training d…
Towards Safety Verification of Direct Perception Neural Networks
Chih-Hong Cheng, Chung-Hao Huang, Thomas Brunner +1
We study the problem of safety verification of direct perception neural networks, where camera images are used as inputs to produce high-level features for autonomous vehicles to m…
Architecting Dependable Learning-enabled Autonomous Systems: A Survey
Chih-Hong Cheng, Dhiraj Gulati, Rongjie Yan
We provide a summary over architectural approaches that can be used to construct dependable learning-enabled autonomous systems, with a focus on automated driving. We consider thre…
Quantitative Projection Coverage for Testing ML-enabled Autonomous Systems
Chih-Hong Cheng, Chung-Hao Huang, Hirotoshi Yasuoka
Systematically testing models learned from neural networks remains a crucial unsolved barrier to successfully justify safety for autonomous vehicles engineered using data-driven ap…
Verification of Binarized Neural Networks via Inter-Neuron Factoring
Chih-Hong Cheng, Georg Nührenberg, Chung-Hao Huang +1
We study the problem of formal verification of Binarized Neural Networks (BNN), which have recently been proposed as a energy-efficient alternative to traditional learning networks…
Neural Networks for Safety-Critical Applications - Challenges, Experiments and Perspectives
Chih-Hong Cheng, Frederik Diehl, Yassine Hamza +5
We propose a methodology for designing dependable Artificial Neural Networks (ANN) by extending the concepts of understandability, correctness, and validity that are crucial ingred…
Automated Analysis of Multi-View Software Architectures
Chih-Hong Cheng, Yassine Hamza, Harald Ruess
Software architectures usually are comprised of different views for capturing static, runtime, and deployment aspects. What is currently missing, however, are formal validation and…
Semantic Degrees for Industrie 4.0
Chih-Hong Cheng, Tuncay Guelfirat, Christian Messinger +3
Under the context of Industrie 4.0 (I4.0), future production systems provide balanced operations between manufacturing flexibility and efficiency, realized in an autonomous, horizo…
Formal Consistency Checking over Specifications in Natural Languages
Rongjie Yan, Chih-Hong Cheng, Guangquan Zhang +1
Early stages of system development involve outlining desired features such as functionality, availability, or usability. Specifications are derived from these features that concret…
Numerical LTL Synthesis for Cyber-Physical Systems
Chih-Hong Cheng, Edward A. Lee
Cyber-physical systems (CPS) are systems that interact with the physical world via sensors and actuators. In such a system, the reading of a sensor represents measures of a physica…