Shaoru Chen's repositories
Polytopic-SLSMPC
Implement SLS MPC for linear systems subject to polytopic model uncertainty and additive disturbances.
Lumped-Uncertainty-SLS-MPC
Robust model predictive control of uncertain linear dynamical systems subject to polytopic model uncertainty and additive disturbances.
time-delay-robust-SLS-MPC
Robust model predictive control of discrete-time time-delay systems using System Level Synthesis (linear time-varying state feedback controllers).
NN-System-PSF
Solving a constrained robust optimal control problem with uncertain neural network dynanmics through convex optimization.
Composite_CBF
Learn a neural network control barrier function subject to safety constraints composited by logical operations.
Learning-NN-ROA
A cutting-plane method to synthesize Lyapunov functions for neural network uncertain systems.
NN-System-Reachability
Finite-step reachable set over-approximation of NN dynamical systems using the one-shot and recursive methods.
deeplearning-models
A collection of various deep learning architectures, models, and tips
alpha-beta-CROWN
alpha-beta-CROWN: An Efficient, Scalable and GPU Accelerated Neural Network Verifier (winner of VNN-COMP'21)
auto_LiRPA
[NeurIPS 2020]auto_LiRPA: An Automatic Linear Relaxation based Perturbation Analysis Library for Neural Networks
cartpole
OpenAI's cartpole env solver.
CartPoleSimulation
This repository contains CartPole simulator with its GUI, implemented controller (LQR) and generator of random desired position trace. It also contains files to train and test RNN predicting future states of a CartPole.
convex_adversarial
A method for training neural networks that are provably robust to adversarial attacks.
decomposition-plnn-bounds
Dual iterative algorithms for Neural Network output bounds computations
gym
A toolkit for developing and comparing reinforcement learning algorithms.
keras-rl
Deep Reinforcement Learning for Keras.
keras-rl2
Reinforcement learning with tensorflow 2 keras
learning-cbfs
Code needed to reproduce the examples found in "Learning Control Barrier Functions from Expert Demonstrations," by A. Robey, H. Hu, L. Lindemann, H. Zhang, D. V. Dimarogonas, S. Tu, and N. Matni, https://arxiv.org/abs/2004.03315
Neural-Barrier-Function
Learn a NN vector barrier function with a convex optimization-based fine-tuning step.
neural-network-lyapunov
Synthesizing neural-network Lyapunov functions (and controllers) as stability certificate.
PWA-Control
Control of piecewise affine systems
reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
SA_DQN
[NeurIPS 2020, Spotlight] State-Adversarial DQN (SA-DQN) for robust deep reinforcement learning
ShaoruChen.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes