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Property Prediction

Property prediction involves forecasting or estimating a molecule's inherent physical and chemical properties based on information derived from its structural characteristics. It facilitates high-throughput evaluation of an extensive array of molecular properties, enabling the virtual screening of compounds. Additionally, it provides the means to predict the unknown attributes of new molecules, thereby bolstering research efficiency and reducing development times.

Papers

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Showing 576–600 of 691 papers

TitleStatusHype
Generalization and Robustness Implications in Object-Centric LearningCode1
On Graph Neural Network Ensembles for Large-Scale Molecular Property PredictionCode0
GeoT: A Geometry-aware Transformer for Reliable Molecular Property Prediction and Chemically Interpretable Representation LearningCode0
Speech2Properties2Gestures: Gesture-Property Prediction as a Tool for Generating Representational Gestures from Speech—0
LiteGEM: Lite Geometry Enhanced Molecular Representation Learning for Quantum Property Prediction—0
DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life ScienceCode1
Dual-view Molecule Pre-trainingCode1
Fast Quantum Property Prediction via Deeper 2D and 3D Graph NetworksCode1
Simple GNN Regularisation for 3D Molecular Property Prediction & BeyondCode1
Flexible dual-branched message passing neural network for quantum mechanical property prediction with molecular conformationCode0
ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction—0
Artificial Intelligence in Drug Discovery: Applications and TechniquesCode1
MoleHD: Ultra-Low-Cost Drug Discovery using Hyperdimensional Computing—0
SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural NetworksCode1
Meta-Learning with Fewer Tasks through Task InterpolationCode1
Materials Representation and Transfer Learning for Multi-Property PredictionCode1
Multipath Graph Convolutional Neural NetworksCode0
Ranking Structured Objects with Graph Neural NetworksCode0
MEG: Generating Molecular Counterfactual Explanations for Deep Graph NetworksCode1
Which Hyperparameters to Optimise? An Investigation of Evolutionary Hyperparameter Optimisation in Graph Neural Network For Molecular Property Prediction—0
Copolymer Informatics with Multi-Task Deep Neural NetworksCode1
Knowledge-aware Contrastive Molecular Graph Learning—0
Molecular Representation Learning by Leveraging Chemical Information—0
Structure-Enhanced Meta-Learning For Few-Shot Graph ClassificationCode0
Assigning Confidence to Molecular Property PredictionCode1
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