activity
20192022
most citedVerification in the Loop: Correct-by-Construction Control Learning with Reach-avoid Guarantees

5 citations · 7 across the 5 of their papers we have counts for

collaborators

8 papers

cs.RO2022

Physics-Aware Safety-Assured Design of Hierarchical Neural Network based Planner

Xiangguo Liu, Chao Huang, Yixuan Wang +2

Neural networks have shown great promises in planning, control, and general decision making for learning-enabled cyber-physical systems (LE-CPSs), especially in improving performan…

eess.SY20215 cited

Verification in the Loop: Correct-by-Construction Control Learning with Reach-avoid Guarantees

Yixuan Wang, Chao Huang, Zhaoran Wang +2

In the current control design of safety-critical autonomous systems, formal verification techniques are typically applied after the controller is designed to evaluate whether the r…

eess.SY20211 cited

Learning-based Framework for Sensor Fault-Tolerant Building HVAC Control with Model-assisted Learning

Shichao Xu, Yangyang Fu, Yixuan Wang +2

As people spend up to 87% of their time indoors, intelligent Heating, Ventilation, and Air Conditioning (HVAC) systems in buildings are essential for maintaining occupant comfort a…

eess.SY20211 cited

Cocktail: Learn a Better Neural Network Controller from Multiple Experts via Adaptive Mixing and Robust Distillation

Yixuan Wang, Chao Huang, Zhilu Wang +3

Neural networks are being increasingly applied to control and decision-making for learning-enabled cyber-physical systems (LE-CPSs). They have shown promising performance without r…

cs.LG2021

Weak Adaptation Learning -- Addressing Cross-domain Data Insufficiency with Weak Annotator

Shichao Xu, Lixu Wang, Yixuan Wang +1

Data quantity and quality are crucial factors for data-driven learning methods. In some target problem domains, there are not many data samples available, which could significantly…

eess.SY2020

Energy-Efficient Control Adaptation with Safety Guarantees for Learning-Enabled Cyber-Physical Systems

Yixuan Wang, Chao Huang, Qi Zhu

Neural networks have been increasingly applied for control in learning-enabled cyber-physical systems (LE-CPSs) and demonstrated great promises in improving system performance and…