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AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
Platform to experiment with the AI Software Engineer. Terminal based. NOTE: Very different from https://gptengineer.app
A toolkit for developing and comparing reinforcement learning algorithms.
Graph Neural Network Library for PyTorch
Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.
Bayesian Modeling and Probabilistic Programming in Python
Matplotlib styles for scientific plotting
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKT…
[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"
A community based Python library for quantitative economics
Benchmark datasets, data loaders, and evaluators for graph machine learning
Automated Red Team Infrastructure deployement using Docker
PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.
A pytorch adversarial library for attack and defense methods on images and graphs
Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
Matplotlib style sheets to nicely format figures for scientific papers, thesis and presentations while keeping them fully editable in Adobe Illustrator.
Code for the paper "Emergent Complexity via Multi-agent Competition"
Library for exploring and validating machine learning data
Recipe for a General, Powerful, Scalable Graph Transformer
The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""
Learn the fundamentals behind one of the most popular web frameworks in the world: Django. We will teach you step-by-step how to implement concepts like Views, Template Rendering, Forms, Saving Dat…
A Deep-Reinforcement Learning Approach for Software-Defined Networking Routing Optimization
An environment for testing AI pentesting agents against a simulated network.
SDN networks (Software Defined Networking ) are exposed to new security threats and attacks, especially Distributed Denial of Service (DDoS) attacks. For this aim, we have proposed a model able to …