L'account GitHub di google-research ospita una vasta gamma di repository pubblici, contribuendo significativamente alla ricerca nel campo dell'intelligenza artificiale e del machine learning. Tra i progetti più noti ci sono bert, google-research e tuning_playbook, con linguaggi principali come Python e Jupyter Notebook, oltre a Shell e C++.
TensorFlow code and pre-trained models for BERT
Google Research
A playbook for systematically maximizing the performance of deep learning models.
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
Nessuna descrizione fornita per questo repository.
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"
SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners
Scenic: A Jax Library for Computer Vision Research and Beyond
Check out the new game server:
Official codebase used to develop Vision Transformer, SigLIP, MLP-Mixer, LiT and more.
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
FILM: Frame Interpolation for Large Motion, In ECCV 2022.
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A data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as instance segmentation masks, depth maps, and optical flow.
Shared repository for open-sourced projects from the Google AI Language team.
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disentanglement_lib is an open-source library for research on learning disentangled representations.
Learning Latent Dynamics for Planning from Pixels
[CVPR 2022 Oral] Official repository for "MAXIM: Multi-Axis MLP for Image Processing". SOTA for denoising, deblurring, deraining, dehazing, and enhancement.
Fast & Simple Resource-Constrained Learning of Deep Network Structure
Official JAX implementation of MAGVIT: Masked Generative Video Transformer
Pix2Seq codebase: multi-tasks with generative modeling (autoregressive and diffusion)
[NeurIPS'21 Outstanding Paper] Library for reliable evaluation on RL and ML benchmarks, even with only a handful of seeds.
AndroidWorld is an environment and benchmark for autonomous agents
A Configurable Recommender Systems Simulation Platform
A collection of Google research projects related to Federated Learning and Federated Analytics.
[CoRL '23] Dexterous piano playing with deep reinforcement learning.
Dream to Control: Learning Behaviors by Latent Imagination
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A benchmark for the next generation of data-driven global weather models.
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Recipes for reproducing Analysis-Ready & Cloud Optimized (ARCO) ERA5 datasets.
Learning to Prompt (L2P) for Continual Learning @ CVPR22 and DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning @ ECCV22
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PDFM Embeddings: location-based vectors for geo-spatial analysis.
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Suite of human-collected datasets and a multi-task continuous control benchmark for open vocabulary visuolinguomotor learning.
Splat-SLAM: Globally Optimized RGB-only SLAM with 3D Gaussians
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Code for the paper "Defeating Prompt Injections by Design"
Learning from synthetic data - code and models
Machine learning models and utilities for exoplanet science.
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This is the official code release for SPARF: Neural Radiance Fields from Sparse and Noisy Poses [CVPR 2023-Highlight]
Falken provides developers with a service that allows them to train AI that can play their games
Modular, scalable library to train ML models
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Code associated with the paper An AI system to help scientists write expert-level empirical software
Python library which enables complex compositions of language models such as scratchpads, chain of thought, tool use, selection-inference, and more.
A modular framework for evaluating weather forecasts
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Deep networks for protein functional inference
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SKAI is a machine learning based tool for performing automatic building damage assessments on aerial imagery of disaster sites.
[ECCV'24] Official Implementation of SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance
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Tools for evaluating the performance of MT metrics on data from recent WMT metrics shared tasks.
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems
E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.
CoReNet is a technique for joint multi-object 3D reconstruction from a single RGB image.
Tooling for agile modeling on large machine perception embedding databases.
Repo for CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning
[NeurIPS 2022] Open source code for reusing prior computational work in RL.
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Code and data accompanying the paper "TRUE: Re-evaluating Factual Consistency Evaluation".
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PaperOrchestra is a multi-agent framework for automated AI research paper writing.
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Semi-supervised anomaly detection method
Finite-state script normalization and processing utilities
Finite-state Transducer (FST) Library.
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This is the official code release for “M2SVid: End-to-End Inpainting and Refinement for Monocular-to-Stereo Video Conversion”. 3DV 2026
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Official implementation of the paper "Increasing Confidence in Adversarial Robustness Evaluations"
SLIP is a sandbox environment for engineering protein sequences with synthetic fitness functions.
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Look Back When Surprised: Stabilizing Reverse Experience Replay for Neural Approximation
Shared MuJoCo simulation scenes and assets for ROBEL environments.
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T2J-Bench is a benchmark for semantic-preserving codebase conversion.
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google-research sviluppa una varietà di progetti, inclusi modelli di deep learning e strumenti per la ricerca in intelligenza artificiale. Progetti come bert e tuning_playbook sono esempi rappresentativi delle loro iniziative.
google-research utilizza principalmente Python e Jupyter Notebook per lo sviluppo dei suoi progetti, ma anche Shell, C++, TeX e TypeScript sono linguaggi frequenti nelle loro repository.
Sì, tutte le repository di google-research sono pubbliche. Questo consente a ricercatori e sviluppatori di accedere ai loro progetti e contribuire alla comunità open source.
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