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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
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
Self-Supervised Speech Pre-training and Representation Learning Toolkit
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".
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 🖼️ & 🖋️
Unified Training of Universal Time Series Forecasting Transformers