Various machine learning implementations and tools

Engineer-To-Order (ETO) Graph Neural Scheduling (GNS) Project

This repository features my solution for the DevFest '24 Challenge by @GDGAlgiers , where I used Proximal Policy Optimization (PPO) to optimize bandwidth allocation based on user demands over 24 hours. Key highlights include dynamic resource allocation and visualizations of demand versus allocation cycles

An implementation of Phasic Policy Gradient, a proposed improvement of Proximal Policy Gradients, in Pytorch

A Torch Based RL Framework for Rapid Prototyping of Research Papers

Simple and Modular implementation of Proximal Policy Optimization (PPO) in PyTorch

Proximal Policy Optimization with Model-Agnostic Meta-Learning for Battery Energy Storage System Management in a Multi-Microgrid

Code for the manuscript "Optimizing ZX-Diagrams with Deep Reinforcement Learning", Maximilian Nägele and Florian Marquardt 2024 Mach. Learn.: Sci. Technol. 5 035077

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

JAX Implementation of Proximal Policy Optimisation Algorithm

Pytorch implementation of Proximal Policy Optimization (PPO) for discrete action spaces

SimplyPPO replicates Proximal-Policy-Optimization with minimum (~250) lines of code in clean, readable PyTorch style, while trying to use as few additional tricks and hyper-parameters as possible (PyBullet benchmarks included).

Balancing a Ball with Reinforcement Learning

A Proximal Policy Optimization Approach to Detect Spoofing in Algorithmic Trading

PPO implementation for controlling a humanoid in Gymnasium's Mujoco environment, featuring customizable training scripts and multi-environment parallel training.

Gymnasium car environment. Autonomous Racing with Proximal Policy Optimization and custom tracks.

Minimal implementation of Proximal Policy Optimization (PPO) in PyTorch

Numerical Evidence for Sample Efficiency of Model-Based over Model-Free Reinforcement Learning Control of Partial Differential Equations [ECC'24]

✨ Solve multi_dimensional multiple knapsack problem using state_of_the_art Reinforcement Learning Algorithms and transformers

Official PyTorch implementation of ExpGen (NeurIPS'23).