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AlphaGenome, accessible via API, cracks the “junk DNA” code, outperforms top rivals in key tests, and puts advanced genomics ...

AllSpice's platform sits between existing workflow software. It allows hardware teams to collaborate on the types of ...

CL-GNN utilizes a contrastive learning strategy, a form of SSL, to learn from a large data set of 371 458 unique unlabeled protein–ligand complexes. By employing graph neural networks and molecular ...

Self-supervised contrastive learning is a powerful pretraining framework for learning the invariant features from the different views of remote sensing images, therefore, the performance of ...

Deep contrastive clustering has recently gained significant attention due to its advantageous ability to leverage the contrastive learning paradigm for joint representation learning and clustering.

This is the official implementation of the paper Lesion-based Contrastive Learning for Diabetic Retinopathy Grading from Fundus Images. - YijinHuang/Lesion-based-Contrastive-Learning ...

Here are some of the top frameworks for contrastive learning. SimCLR. Developed by Google, SimCLR is an open-source framework for advancing self-supervised and semi-supervised models for image ...

Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval. ICLR2021. Authors:Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, Arnold ...