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Found 3 papers, 3 papers with code
Interpretable Deep Learning in Drug Discovery
Without any means of interpretation, neural networks that predict molecular properties and bioactivities are merely black boxes.
Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery
We propose a novel distance measure between two sets of molecules, called Fr\'echet ChemNet distance (FCD), that can be used as an evaluation metric for generative models.
DeepSynergy: Predicting Anti-Cancer Drug Synergy with Deep Learning
While drug combination therapies are a well-established concept in cancer treatment, identifying novel synergistic combinations is challenging due to the size of combinatorial space.
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