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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 101–150 of 691 papers

TitleStatusHype
Interactive Molecular Discovery with Natural LanguageCode1
Automated 3D Pre-Training for Molecular Property PredictionCode1
CrysMMNet: Multimodal Representation for Crystal Property PredictionCode1
GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot LearningCode1
Learning Large Graph Property Prediction via Graph Segment TrainingCode1
O-GNN: Incorporating Ring Priors into Molecular ModelingCode1
Molecule-Morphology Contrastive Pretraining for Transferable Molecular RepresentationCode1
SELFormer: Molecular Representation Learning via SELFIES Language ModelsCode1
A new perspective on building efficient and expressive 3D equivariant graph neural networksCode1
Learning Harmonic Molecular Representations on Riemannian ManifoldCode1
Data-Centric Learning from Unlabeled Graphs with Diffusion ModelCode1
Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human LanguageCode1
Learning Topology-Specific Experts for Molecular Property PredictionCode1
Retrieved Sequence Augmentation for Protein Representation LearningCode1
GPS++: Reviving the Art of Message Passing for Molecular Property PredictionCode1
CrysGNN : Distilling pre-trained knowledge to enhance property prediction for crystalline materialsCode1
HAC-Net: A Hybrid Attention-Based Convolutional Neural Network for Highly Accurate Protein-Ligand Binding Affinity PredictionCode1
Pushing the boundaries of molecular property prediction for drug discovery with multitask learning BERT enhanced by SMILES enumerationCode1
Implicit Convolutional Kernels for Steerable CNNsCode1
Heterogenous Ensemble of Models for Molecular Property PredictionCode1
Bidirectional Generation of Structure and Properties Through a Single Molecular Foundation ModelCode1
GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property PredictionCode1
ParticleGrid: Enabling Deep Learning using 3D Representation of MaterialsCode1
Materials Property Prediction with Uncertainty Quantification: A Benchmark StudyCode1
MOFormer: Self-Supervised Transformer model for Metal-Organic Framework Property PredictionCode1
OQM9HK: A Large-Scale Graph Dataset for Machine Learning in Materials ScienceCode1
polyBERT: A chemical language model to enable fully machine-driven ultrafast polymer informaticsCode1
Unraveling Key Elements Underlying Molecular Property Prediction: A Systematic StudyCode1
Periodic Graph Transformers for Crystal Material Property PredictionCode1
A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural LanguageCode1
TransPolymer: a Transformer-based language model for polymer property predictionsCode1
HiGNN: Hierarchical Informative Graph Neural Networks for Molecular Property Prediction Equipped with Feature-Wise AttentionCode1
Semi-Supervised Junction Tree Variational Autoencoder for Molecular Property PredictionCode1
A Gaze into the Internal Logic of Graph Neural Networks, with LogicCode1
Deep learning-based denoising for fast time-resolved flame emission spectroscopy in high-pressure combustion environmentCode1
FunQG: Molecular Representation Learning Via Quotient GraphsCode1
Unified 2D and 3D Pre-Training of Molecular RepresentationsCode1
Graph Property Prediction on Open Graph Benchmark: A Winning Solution by Graph Neural Architecture SearchCode1
Graph-based Molecular Representation LearningCode1
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide ElectrocatalystsCode1
LIMO: Latent Inceptionism for Targeted Molecule GenerationCode1
Graph Rationalization with Environment-based AugmentationsCode1
Shortest Path Networks for Graph Property PredictionCode1
KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property PredictionCode1
Pre-training via Denoising for Molecular Property PredictionCode1
A graph representation of molecular ensembles for polymer property predictionCode1
Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property PredictionCode1
Learning to Split for Automatic Bias DetectionCode1
Naturally-meaningful and efficient descriptors: machine learning of material properties based on robust one-shot ab initio descriptorsCode1
Structured Multi-task Learning for Molecular Property PredictionCode1
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