MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments

recipe for training fully-featured self supervised image jepa models

Official PyTorch implementation of MOOD series: (1) MOODv1: Rethinking Out-of-distributionDetection: Masked Image Modeling Is All You Need. (2) MOODv2: Masked Image Modeling for Out-of-Distribution…

PyTorch implementation of BEVT (CVPR 2022) https://arxiv.org/abs/2112.01529

Code for the paper: Masked Image Modeling as a Framework for Self-Supervised Learning across Eye Movements

This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".

This is a PyTorch implementation of “Context AutoEncoder for Self-Supervised Representation Learning"

🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading

Code for ICLR 2024 (Spotlight) paper "MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding"

[ECCV 2024] PDiscoFormer: Relaxing Part Discovery Constraints with Vision Transformers

Learning to Detect and Segment Mobile Objects from Unlabeled Videos

Experiments in Joint Embedding Predictive Architectures (JEPAs).

Pytorch implementation of an energy transformer - an energy-based reccurrent variant of the transformer.

Self-Supervised Learning in PyTorch

Github repo with tutorials to fine tune transformers for diff NLP tasks

Creates subsets of ImageNet (e.g. ImageNet100)

[ICLR2024] Exploring Target Representations for Masked Autoencoders

A Contrastive Learning Boost from Intermediate Pre-Trained Representations

A Simple but Powerful SOTA NER Model | Official Code For Label Supervised LLaMA Finetuning

The latest research progress of Contrastive Learning(CL), Data Augmentation(DA) and Self-Supervised Learning(SSL) in Recommender Systems

A curated list of resources for Learning with Noisy Labels

An optimized implementation of masked autoencoders (MAEs)

Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).

Implementations of various Self Supervised Learning methods

Supplementary material and code for "Conformal Credal Self-Supervised Learning" as published at COPA 2021.

Physics guided dual self-supervised learning for materials property prediction

A collection of research materials on SSL for non-sequential tabular data (SSL4NSTD)

This repository contains a collection of resources and papers on GNN Models on Crystal Solid State Materials