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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:

  • Use GitHub editor to open the project. To open the editor change the url from github.com to github.dev in the address bar.
  • In the left navigation panel, right-click on the folder of interest and select download.

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

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.

semivl icon semivl

[ECCV'24] Official Implementation of SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance

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.

snap icon snap

SNAP: Self-supervised Neural Maps for Visual Positioning and Semantic Understanding (NeurIPS 2023)

sofima icon sofima

Scalable Optical Flow-based Image Montaging and Alignment

sparf icon sparf

This is the official code release for SPARF: Neural Radiance Fields from Sparse and Noisy Poses [CVPR 2023-Highlight]

sputnik icon sputnik

A library of GPU kernels for sparse matrix operations.

swift-tfp icon swift-tfp

Find shape errors before you run your code!

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