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Google Research

This repository contains code released by Google Research.

All datasets in this repository are released under the CC BY 4.0 International license, which can be found here: https://creativecommons.org/licenses/by/4.0/legalcode. All source files in this repository are released under the Apache 2.0 license, the text of which can be found in the LICENSE file.


Because the repo is large, we recommend you download only the subdirectory of interest:

SUBDIR=foo
svn export https://github.com/google-research/google-research/trunk/$SUBDIR

If you'd like to submit a pull request, you'll need to clone the repository; we recommend making a shallow clone (without history).

git clone [email protected]:google-research/google-research.git --depth=1

Disclaimer: This is not an official Google product.

Updated in 2023.

Google Research's Projects

rigl icon rigl

End-to-end training of sparse deep neural networks with little-to-no performance loss.

rl-reliability-metrics icon rl-reliability-metrics

The RL Reliability Metrics library provides a set of metrics for measuring the reliability of reinforcement learning (RL) algorithms, as well as statistical tools for comparing algorithms and for computing confidence intervals on these metrics.

rlds-creator icon rlds-creator

A web-based tool to collect human data from simulated environments.

rliable icon rliable

[NeurIPS'21 Outstanding Paper] Library for reliable evaluation on RL and ML benchmarks, even with only a handful of seeds.

robel icon robel

ROBEL: Robotics Benchmarks for Learning with low-cost robots

robel-scenes icon robel-scenes

Shared MuJoCo simulation scenes and assets for ROBEL environments.

runtime-error-prediction icon runtime-error-prediction

This is the repository for the paper Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions, and for the Python Runtime Errors (PRE) dataset.

s4l icon s4l

Tensorflow implementation of S4L: Self-Supervised Semi-Supervised Learning

scenic icon scenic

Scenic: A Jax Library for Computer Vision Research and Beyond

se3ds icon se3ds

This repository hosts the code for our paper, "Simple and Effective Synthesis of Indoor 3D Scenes".

seed_rl icon seed_rl

SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.

simclr icon simclr

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

skai icon skai

SKAI is a machine learning based tool for performing automatic building damage assessments on aerial imagery of disaster sites.

slip icon slip

SLIP is a sandbox environment for engineering protein sequences with synthetic fitness functions.

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