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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 101–125 of 691 papers

TitleStatusHype
A new perspective on building efficient and expressive 3D equivariant graph neural networksCode1
Learning Invariances in Neural NetworksCode1
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property PredictionCode1
3D-MolT5: Leveraging Discrete Structural Information for Molecule-Text ModelingCode1
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property PredictionCode1
Chemical-Reaction-Aware Molecule Representation LearningCode1
Graph Neural Networks Need Cluster-Normalize-Activate ModulesCode1
ChemLLM: A Chemical Large Language ModelCode1
Any-Property-Conditional Molecule Generation with Self-Criticism using Spanning TreesCode1
ChiENN: Embracing Molecular Chirality with Graph Neural NetworksCode1
Graph Rationalization with Environment-based AugmentationsCode1
HAC-Net: A Hybrid Attention-Based Convolutional Neural Network for Highly Accurate Protein-Ligand Binding Affinity PredictionCode1
Generalization and Robustness Implications in Object-Centric LearningCode1
Global Concept Explanations for Graphs by Contrastive LearningCode1
A Gaze into the Internal Logic of Graph Neural Networks, with LogicCode1
MAMMAL -- Molecular Aligned Multi-Modal Architecture and LanguageCode1
CrysGNN : Distilling pre-trained knowledge to enhance property prediction for crystalline materialsCode1
Generative Pre-Training from MoleculesCode1
CrysMMNet: Multimodal Representation for Crystal Property PredictionCode1
Comparison of Atom Representations in Graph Neural Networks for Molecular Property PredictionCode1
GeomGCL: Geometric Graph Contrastive Learning for Molecular Property PredictionCode1
Geometric Transformer for End-to-End Molecule Properties PredictionCode1
Artificial Intelligence in Drug Discovery: Applications and TechniquesCode1
GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot LearningCode1
Copolymer Informatics with Multi-Task Deep Neural NetworksCode1
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