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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 151–200 of 691 papers

TitleStatusHype
A community-powered search of machine learning strategy space to find NMR property prediction modelsCode1
Deep learning-based denoising for fast time-resolved flame emission spectroscopy in high-pressure combustion environmentCode1
AugLiChem: Data Augmentation Library of Chemical Structures for Machine LearningCode1
Improving VAE based molecular representations for compound property predictionCode1
InversionGNN: A Dual Path Network for Multi-Property Molecular OptimizationCode1
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and moleculesCode1
A Cartesian Encoding Graph Neural Network for Crystal Structures Property Prediction: Application to Thermal Ellipsoid EstimationCode1
KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property PredictionCode1
Generative Pre-Training from MoleculesCode1
3D Infomax improves GNNs for Molecular Property PredictionCode1
Automated 3D Pre-Training for Molecular Property PredictionCode1
Directed Graph Grammars for Sequence-based LearningCode1
AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool UseCode1
Contrastive Dual-Interaction Graph Neural Network for Molecular Property PredictionCode1
LLaMo: Large Language Model-based Molecular Graph AssistantCode1
LLM4Mat-Bench: Benchmarking Large Language Models for Materials Property PredictionCode1
MAMMAL -- Molecular Aligned Multi-Modal Architecture and LanguageCode1
Materials Informatics Transformer: A Language Model for Interpretable Materials Properties PredictionCode1
Materials Representation and Transfer Learning for Multi-Property PredictionCode1
MD-HIT: Machine learning for materials property prediction with dataset redundancy controlCode1
Bayesian Graph Neural Networks for Molecular Property PredictionCode1
Explaining Deep Graph Networks with Molecular CounterfactualsCode1
ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property PredictionCode1
Improving Molecular Representation Learning with Metric Learning-enhanced Optimal TransportCode1
Few-Shot Graph Learning for Molecular Property PredictionCode1
MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property PredictionCode1
Dual-view Molecule Pre-trainingCode1
Molecular machine learning with conformer ensemblesCode1
Dynamic In-context Learning with Conversational Models for Data Extraction and Materials Property PredictionCode1
A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural LanguageCode1
GEOM: Energy-annotated molecular conformations for property prediction and molecular generationCode1
Molecule-Morphology Contrastive Pretraining for Transferable Molecular RepresentationCode1
Multimodal Foundation Models for Material Property Prediction and DiscoveryCode1
GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and TextCode1
Graph Transformers for Large GraphsCode1
Multi-view biomedical foundation models for molecule-target and property predictionCode1
An algorithmic framework for synthetic cost-aware decision making in molecular designCode1
Neural Message Passing for Quantum ChemistryCode1
E(n) Equivariant Topological Neural NetworksCode1
Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human LanguageCode1
Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph LanguagesCode1
Fragment-based Pretraining and Finetuning on Molecular GraphsCode1
Can Large Language Models Empower Molecular Property Prediction?Code1
Generalization and Robustness Implications in Object-Centric LearningCode1
PeptideBERT: A Language Model based on Transformers for Peptide Property PredictionCode1
Periodic Graph Transformers for Crystal Material Property PredictionCode1
MMPolymer: A Multimodal Multitask Pretraining Framework for Polymer Property PredictionCode1
3DReact: Geometric deep learning for chemical reactionsCode1
Learning Molecular Representation in a CellCode1
Pairwise Learning for Neural Link PredictionCode1
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