An educational resource to help anyone learn deep reinforcement learning.

Implementation of Graph Convolutional Networks in TensorFlow

SGLang is a fast serving framework for large language models and vision language models.

Build Graph Nets in Tensorflow

Sequence modeling benchmarks and temporal convolutional networks

🔥 TensorFlow Code for technical report: "YOLOv3: An Incremental Improvement"

Representation learning on large graphs using stochastic graph convolutions.

An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities

Dual Attention Network for Scene Segmentation (CVPR2019)

Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

PyTorch implementation of SENet

The devkit of the nuScenes dataset.

VGG19 and VGG16 on Tensorflow

A CV toolkit for my papers.

Python Multi-Agent Reinforcement Learning framework

tensorflow implementation of 'YOLO : Real-Time Object Detection'

Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

Restricted Boltzmann Machines in Python.

Reinforcement Learning environments for Traffic Signal Control with SUMO. Compatible with Gymnasium, PettingZoo, and popular RL libraries.

Deep learning toolbox based on PyTorch for hyperspectral data classification.

Constrained Policy Optimization

A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm

Implementation of the real-time MPC based on iLQR in Carla simulator

POMDPs in Python.

SIMPL: A Simple and Efficient Multi-agent Motion Prediction Baseline for Autonomous Driving

Yolo v3 object detection implemented in Tensorflow.

This is the repository of the F1TENTH Gym environment.

🚀 A fast safe reinforcement learning library in PyTorch