molecular graph

Learning Graph Models for Retrosynthesis Prediction NeurIPS 2021 Neural representation and generation for RNA secondary structures ICLR 2021 Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction ICML 2021 SafeDrug: Dual Molecular Graph Encoders for Recommending Effective and Safe Drug Combinations IJCAI 2021 A Deep Generative Model for Fragment-Based Molecule Generation AISTATS 2020 A Graph to Graphs Framework for Retrosynthesis Prediction ICML 2020 Building powerful and equivariant graph neural networks with structural message-passing NeurIPS 2020 Chemically Interpretable Graph Interaction Network for Prediction of Pharmacokinetic Properties of Drug-Like Molecules AAAI 2020 Communicative Representation Learning on Attributed Molecular Graphs IJCAI 2020 Directional Message Passing for Molecular Graphs ICLR 2020 GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation ICML 2020 Hierarchical Generation of Molecular Graphs using Structural Motifs ICML 2020 NEVAE: A Deep Generative Model for Molecular Graphs JMLR 2020 On the equivalence of molecular graph convolution and molecular wave function with poor basis set NeurIPS 2020 Reinforcement Learning for Molecular Design Guided by Quantum Mechanics ICML 2020 RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist NeurIPS 2020 Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective AAAI 2019 NeVAE: A Deep Generative Model for Molecular Graphs AAAI 2019 Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders NeurIPS 2018 Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation NeurIPS 2018 Deriving Neural Architectures from Sequence and Graph Kernels ICML 2017 Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network NeurIPS 2017