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Name: Meta Research
Type: Organization
Location: Menlo Park, California
Name: Meta Research
Type: Organization
Location: Menlo Park, California
Compression primitives for uplink compression in Federated Learning that are compatible with Secure Aggregation.
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Predicting Deeper into the Future of Semantic Segmentation
This repo covers the implementation for Labelling unlabelled videos from scratch with multi-modal self-supervision, which learns clusters from multi-modal data in a self-supervised way.
Implementation for the CVPR 2023 paper "Improving Selective Visual Question Answering by Learning from Your Peers" (https://arxiv.org/abs/2306.08751)
Code implementing the experiments of "Fixes That Fail Self-Defeating Improvements in Machine-Learning Systems".
Evaluation benchmark for the task of Semantic Image Translation. Contains code to run FlexIT (CVPR 2022)
Code for "SemDeDup", a simple method for identifying and removing semantic duplicates from a dataset (data pairs which are semantically similar, but not exactly identical).
code for "Semi-Discrete Normalizing Flows through Differentiable Tessellation"
Semi-supervised ImageNet1K models
SentAugment is a data augmentation technique for NLP that retrieves similar sentences from a large bank of sentences. It can be used in combination with self-training and knowledge-distillation, or for retrieving paraphrases.
A python tool for evaluating the quality of sentence embeddings.
A shack for hacklang design
NeurIPS 2021: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architectures
Compile-time shape checking and inference in Kotlin for tensor code
This is the repo for the paper Shepherd -- A Critic for Language Model Generation
Fast Differentiable Tensor Library in JavaScript and TypeScript with Bun + Flashlight
The AI Knowledge Editor
Code for the paper Self-Supervised Learning of Split Invariant Equivariant Representations
SiLK (Simple Learned Keypoint) is a self-supervised deep learning keypoint model.
codebase for the SIMAT dataset and evaluation
With the aim of building next generation virtual assistants that can handle multimodal inputs and perform multimodal actions, we introduce two new datasets (both in the virtual shopping domain), the annotation schema, the core technical tasks, and the baseline models. The code for the baselines and the datasets will be opensourced.
Code for SIMMC 2.0: A Task-oriented Dialog Dataset for Immersive Multimodal Conversations
PyTorch implementation of SimSiam https//arxiv.org/abs/2011.10566
SimulEval: A General Evaluation Toolkit for Simultaneous Translation
Symbol-to-Instrument Neural Generator
Learning error bars for neural network predictions
Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees
Code release for SLIP Self-supervision meets Language-Image Pre-training
PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.