Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Reading list for research topics in multimodal machine learning

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

A curated list of network embedding techniques.

EVA Series: Visual Representation Fantasies from BAAI

Self-Supervised Speech Pre-training and Representation Learning Toolkit

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

Datasets, tools, and benchmarks for representation learning of code.

Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org

The implementation of DeBERTa

Cambrian-1 is a family of multimodal LLMs with a vision-centric design.

A collection of research on knowledge graphs

Code for ALBEF: a new vision-language pre-training method

SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]

Code for TKDE paper "Self-supervised learning on graphs: Contrastive, generative, or predictive"

Code for the Interspeech 2021 paper "AST: Audio Spectrogram Transformer".

Unified Training of Universal Time Series Forecasting Transformers

A comprehensive list of awesome contrastive self-supervised learning papers.

GraphVite: A General and High-performance Graph Embedding System

Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts, images, and 🔜 video, up to 5x faster than OpenAI CLIP and LLaVA 🖼️ & 🖋️