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Greatest papers with code

Analyzing Learned Molecular Representations for Property Prediction

2 Apr 2019chemprop/chemprop

In addition, we introduce a graph convolutional model that consistently matches or outperforms models using fixed molecular descriptors as well as previous graph neural architectures on both public and proprietary datasets.

MOLECULAR PROPERTY PREDICTION

Strategies for Pre-training Graph Neural Networks

ICLR 2020 snap-stanford/pretrain-gnns

Many applications of machine learning require a model to make accurate pre-dictions on test examples that are distributionally different from training ones, while task-specific labels are scarce during training.

GRAPH CLASSIFICATION MOLECULAR PROPERTY PREDICTION PROTEIN FUNCTION PREDICTION REPRESENTATION LEARNING

Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective

25 Jun 2019awslabs/dgl-lifesci

In this paper, we propose a generalizable and transferable Multilevel Graph Convolutional neural Network (MGCN) for molecular property prediction.

GRAPH REGRESSION MOLECULAR PROPERTY PREDICTION

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization

ICLR 2020 fanyun-sun/InfoGraph

There are also some recent methods based on language models (e. g. graph2vec) but they tend to only consider certain substructures (e. g. subtrees) as graph representatives.

GRAPH CLASSIFICATION MOLECULAR PROPERTY PREDICTION UNSUPERVISED REPRESENTATION LEARNING

ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

19 Oct 2020seyonechithrananda/bert-loves-chemistry

GNNs and chemical fingerprints are the predominant approaches to representing molecules for property prediction.

MOLECULAR PROPERTY PREDICTION REPRESENTATION LEARNING

Learning Invariances in Neural Networks

22 Oct 2020g-benton/learning-invariances

Invariances to translations have imbued convolutional neural networks with powerful generalization properties.

IMAGE CLASSIFICATION MOLECULAR PROPERTY PREDICTION

Path-Augmented Graph Transformer Network

29 May 2019benatorc/PA-Graph-Transformer

Much of the recent work on learning molecular representations has been based on Graph Convolution Networks (GCN).

MOLECULAR PROPERTY PREDICTION

Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery

2 Dec 2020divelab/MoleculeKit

Here we develop the MoleculeKit, a suite of comprehensive machine learning tools spanning different computational models and molecular representations for molecular property prediction and drug discovery.

DRUG DISCOVERY MOLECULAR PROPERTY PREDICTION

Optimal Transport Graph Neural Networks

8 Jun 2020benatorc/OTGNN

Current graph neural network (GNN) architectures naively average or sum node embeddings into an aggregated graph representation -- potentially losing structural or semantic information.

DRUG DISCOVERY GRAPH REGRESSION MOLECULAR PROPERTY PREDICTION