A minimalist environment for decision-making in autonomous driving

Chronos: Pretrained (Language) Models for Probabilistic Time Series Forecasting

TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

Official PyTorch Implementation of SAGPool - ICML 2019

Object (e.g Pedestrian, vehicles) tracking by Extended Kalman Filter (EKF), with fused data from both lidar and radar sensors.

Python implementations of contextual bandits algorithms

Delay Phased Array - New programmable array with delays and phase shift to generate flexible frequency-dependent beams

18.337 - Parallel Computing and Scientific Machine Learning

The implementation of LSTM-TD3.

A framework for implementing federated learning

FedML - The federated learning and analytics library enabling secure and collaborative machine learning on decentralized data anywhere at any scale. Supporting large-scale cross-silo federated lear…

An Industrial Grade Federated Learning Framework

Flower - A Friendly Federated Learning Framework

A collection of Google research projects related to Federated Learning and Federated Analytics.

🐈‍⬛ Contextual bandits library for continuous action trees with smoothing in JAX

FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai

federated-learning

Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

Reservoir computing utilities for scientific machine learning (SciML)

Papers from the computer science community to read and discuss.

An official JAX-based code for our NeuraLCB paper, "Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization", ICLR 2022.

This repository is a list of machine learning libraries written in Rust. It's a compilation of GitHub repositories, blogs, books, movies, discussions, papers, etc. 🦀

Using RL for anomaly detection in NSL-KDD

Github Repo for CARL: Cautious Adaptation for RL in Safety Critical Settings

Quantum Machine Learning Community Course

benchmarking quantum circuit emulators for your daily research usage

Study NeuralUCB and regret analysis for contextual bandit with neural decision