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Found 4 papers, 1 papers with code
Molecular Property Prediction by Semantic-invariant Contrastive Learning
Contrastive learning have been widely used as pretext tasks for self-supervised pre-trained molecular representation learning models in AI-aided drug design and discovery.
Activity Cliff Prediction: Dataset and Benchmark
In this paper, we first introduce ACNet, a large-scale dataset for AC prediction.
Can Pre-trained Models Really Learn Better Molecular Representations for AI-aided Drug Discovery?
Self-supervised pre-training is gaining increasingly more popularity in AI-aided drug discovery, leading to more and more pre-trained models with the promise that they can extract better feature representations for molecules.
Dissensus Algorithms for Opinion Dynamics on the Sphere
The information of the covariance formed by the opinion state of each agent is used to achieve a dissensus equilibrium on unsigned graphs.
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