Cleora AI is a general-purpose open-source model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data. Created by Synerise.com team.
- ai
- graphs
- synerise
- embeddings
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Learning Heterogeneous Tactile Representation for General Dexterous Manipulation
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.
- artificial-intelligence
- clip
- pathology
- vision-and-language
UCE is a zero-shot foundation model for single-cell gene expression data
BulkFormer: A large-scale foundation model for human bulk transcriptomes
CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer
- cancer
- foundation-model
- single-cell
This is a german ELMo deep contextualized word representation. It is trained on a special German Wikipedia Text Corpus.
- bilm
- elmo
- tensorflow
- machine-learning
A Common Lisp embeddings library
gtfs2vec - Learning GTFS Embeddings for comparing PublicTransport Offer in Microregions