mbchang

data-driven-characters

Generate chatbots from a corpus

meta-prompt

A re-implementation of Meta-Prompt in LangChain for building self-improving agents.

decentralized-rl

Decentralized Reinforcment Learning: Global Decision-Making via Local Economic Transactions (ICML 2020)

panel_simulation

A simulated panel discussion of the AI SF Summit https://aisf.co/

minimal-bayesian-flow-networks

A minimal reproduction of the basic figures of the Bayesian Flow Networks paper for building intuition.

jax-iterative-inference

awesome-ai-agents

A list of AI autonomous agents

langchain

⚡ Building applications with LLMs through composability ⚡

ai-code-refactorer

Use AI to refactor code

c-swm

Contrastive Learning of Structured World Models

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

deq

[NeurIPS'19] Deep Equilibrium Models

dreamer

Dream to Control: Learning Behaviors by Latent Imagination

dreamer-pytorch-yusukeurakami

pytorch-implementation of Dreamer (Model-based Image RL Algorithm)

dreamerv2

Mastering Atari with Discrete World Models

furniture

IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks

google-research

Google Research

hri

ImpSq

Implicit^2: Implicit model for implicit neural representations

kmeans_pytorch

pytorch implementation of basic kmeans algorithm(lloyd method with forgy initialization) with gpu support

KNNRegression

In this project we will be solving KNN Regression problem from scratch. We will be implementing the KNN problem in the naive method using a for loop and also in a vectorised approach using numpy broadcasting. We will also plot the root mean squared error for various K values and chose the optimal number of nearest neighbours.

latex-assistant

magical

The MAGICAL benchmark suite for robust imitation learning (NeurIPS 2020)

mbchang.github.io

mbrl-lib

Library for Model Based RL

multiagent-particle-envs

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

pytorch-a2c-ppo-acktr-gail

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

ravens

Train robotic agents to learn pick and place with deep learning for vision-based manipulation in PyBullet. Transporter Nets, CoRL 2020.

submitit

Python 3.6+ toolbox for submitting jobs to Slurm

vercel-flask-example

Enjoy our curated collection of examples and solutions. Use these patterns to build your own robust and scalable applications.