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Found 5 papers, 5 papers with code
RGCVAE: Relational Graph Conditioned Variational Autoencoder for Molecule Design
Identifying molecules that exhibit some pre-specified properties is a difficult problem to solve.
Weakly-Supervised Visual-Textual Grounding with Semantic Prior Refinement
The first untrained module aims to return a rough alignment between textual phrases and bounding boxes.
A Better Loss for Visual-Textual Grounding
Given a textual phrase and an image, the visual grounding problem is the task of locating the content of the image referenced by the sentence.
Conditional Constrained Graph Variational Autoencoders for Molecule Design
In recent years, deep generative models for graphs have been used to generate new molecules.
A Systematic Assessment of Deep Learning Models for Molecule Generation
In recent years the scientific community has devoted much effort in the development of deep learning models for the generation of new molecules with desirable properties (i. e. drugs).
