yonetaniryo

federated_learning_pytorch

Simplified implementation of federated learning in PyTorch

fmt

Python implementation of Fast Marching Tree

jax-vs-pytorch

Comparisons between PyTorch and JAX (Flax)

neural-astar-jax

Jax implementation of Neural A*

numpy2tfrecord

Simple helper library to convert numpy data to tfrecord and build a tensorflow dataset

yonetaniryo.github.io

jax-heapq

JAX implementation of heapq

starter-academic

🎓 Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify

code-server

VS Code in the browser

ctrm

CTRMs: Learning to Construct Cooperative Timed Roadmaps for Multi-agent Path Planning in Continuous Spaces (AAMAS-22)

diffusion_models

A series of tutorial notebooks on denoising diffusion probabilistic models in PyTorch

flwr_leaf

Example of Flower (Federated Learning Framework) used on LEAF

Focaccia

jaxmapp

JAX-based implementation for multi-agent path planning (MAPP) in continuous spaces.

libbot2

libbot2

macos-terminal-themes

Color schemes for default macOS Terminal.app

multiplicative_controller_fusion

[IROS 2020] Multiplicative Controller Fusion - Leveraging Algorithmic Priors for Sample-efficient Reinforcement Learning and Safe Sim-To-Real Transfer

multipolar

Multi-Source Policy Aggregation for Transfer Reinforcement Learning between Diverse Environmental Dynamics

neural-astar

Official implementation of "Path Planning using Neural A* Search" (ICML-21)

OpenTraj

Human Trajectory Prediction Dataset Benchmark (ACCV 2020)

planning-datasets

Dataset generation scripts for “Path Planning using Neural A* Search” presented in ICML-21

planning_python

prompt2model

prompt2model - Generate Deployable Models from Natural Language Instructions

residual_reactive_navigation

[ICRA 2020] Residual Reactive Navigation: Combining Classical and Learned Navigation Strategies for Deployment in Unknown Environments

SaIL

segmentation_models.pytorch

Segmentation models with pretrained backbones. PyTorch.

ShinRL-1

ShinRL: A Library for Evaluating RL Algorithms from Theoretical and Practical Perspectives (Deep RL Workshop 2021)

test

theia-apps

Theia applications examples - docker images, desktop apps, packagings

TLIO

Tight Learned Inertial Odometry