Pinned Repositories
jaxonnxruntime
A user-friendly tool chain that enables the seamless execution of ONNX models using JAX as the backend.
bark-ml
Gym environments and agents for autonomous driving.
cem-torch
Cross Entropy Method (CEM) implemented under Pytorch, supporting batch dimension and receding horizon style optimization.
cvpo-safe-rl
Code for "Constrained Variational Policy Optimization for Safe Reinforcement Learning" (ICML 2022)
d3rlpy
An offline deep reinforcement learning library
decision-transformer
handful-of-trials
Experiment code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"
Interaction-aware-Trajectory-Prediction
A selection of state-of-the-art research materials on trajectory prediction
safe-sb3
saferl-envs
jinning-li's Repositories
jinning-li/Interaction-aware-Trajectory-Prediction
A selection of state-of-the-art research materials on trajectory prediction
jinning-li/cem-torch
Cross Entropy Method (CEM) implemented under Pytorch, supporting batch dimension and receding horizon style optimization.
jinning-li/safe-sb3
jinning-li/saferl-envs
jinning-li/bark-ml
Gym environments and agents for autonomous driving.
jinning-li/cvpo-safe-rl
Code for "Constrained Variational Policy Optimization for Safe Reinforcement Learning" (ICML 2022)
jinning-li/d3rlpy
An offline deep reinforcement learning library
jinning-li/decision-transformer
jinning-li/handful-of-trials
Experiment code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"
jinning-li/homework_fall2020
Assignments for Berkeley CS 285: Deep Reinforcement Learning (Fall 2020)
jinning-li/jaxonnxruntime
jinning-li/jinning-li.github.io
jinning-li/ray
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
jinning-li/safe-mbrl
Safe Model-based Reinforcement Learning with Robust Cross-Entropy Method
jinning-li/metadrive
MetaDrive: Composing Diverse Scenarios for Generalizable Reinforcement Learning
jinning-li/omnisafe
OmniSafe is a comprehensive and reliable benchmark for safe reinforcement learning.
jinning-li/safety-gym
Tools for accelerating safe exploration research.
jinning-li/TorchLRP
A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).