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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 601–650 of 691 papers

TitleStatusHype
ApisTox: a new benchmark dataset for the classification of small molecules toxicity on honey beesCode0
Domain-Adversarial Multi-Task Framework for Novel Therapeutic Property Prediction of CompoundsCode0
Large-Scale Knowledge Integration for Enhanced Molecular Property PredictionCode0
Accelerating Material Property Prediction using Generically Complete Isometry InvariantsCode0
Multimodal machine learning with large language embedding model for polymer property predictionCode0
Multimodal Model with Text and Drug Embeddings for Adverse Drug Reaction ClassificationCode0
Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property PredictionCode0
Coarse-Grained Configurational Polymer Fingerprints for Property Prediction using Machine LearningCode0
Multipath Graph Convolutional Neural NetworksCode0
Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide PropertiesCode0
Towards Data-Efficient Pretraining for Atomic Property PredictionCode0
Isotropic Gaussian Processes on Finite Spaces of GraphsCode0
Towards deep generation of guided wave representations for composite materialsCode0
D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation LearningCode0
Interpreting the Syntactic and Social Elements of the Tweet Representations via Elementary Property Prediction TasksCode0
MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-based Protein Structure PredictionCode0
Interpretation of Semantic Tweet RepresentationsCode0
Integrating Predictive and Generative Capabilities by Latent Space Design via the DKL-VAE ModelCode0
Integrating convolutional layers and biformer network with forward-forward and backpropagation trainingCode0
Do Graph Neural Networks Work for High Entropy Alloys?Code0
Towards Faster and More Compact Foundation Models for Molecular Property PredictionCode0
Independent Vector Analysis for Data Fusion Prior to Molecular Property Prediction with Machine LearningCode0
Object-Centric Learning with Slot Mixture ModuleCode0
Improving Molecular Pretraining with Complementary FeaturizationsCode0
An open unified deep graph learning framework for discovering drug leadsCode0
On Graph Neural Network Ensembles for Large-Scale Molecular Property PredictionCode0
Diverse Explanations From Data-Driven and Domain-Driven Perspectives in the Physical SciencesCode0
Unlocking Chemical Insights: Superior Molecular Representations from Intermediate Encoder LayersCode0
Improving Graph Property Prediction with Generalized Readout FunctionsCode0
CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation LearningCode0
Impact of SMILES Notational Inconsistencies on Chemical Language Model PerformanceCode0
Identifying Semantic Component for Robust Molecular Property PredictionCode0
Sliceformer: Make Multi-head Attention as Simple as Sorting in Discriminative TasksCode0
Outlier-Based Domain of Applicability Identification for Materials Property Prediction ModelsCode0
Towards out-of-distribution generalizable predictions of chemical kinetics propertiesCode0
Homomorphism Counts as Structural Encodings for Graph LearningCode0
CL-MFAP: A Contrastive Learning-Based Multimodal Foundation Model for Molecular Property Prediction and Antibiotic ScreeningCode0
PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property PredictionCode0
PatchProt: Hydrophobic patch prediction using protein foundation modelsCode0
Path-Augmented Graph Transformer NetworkCode0
Path-aware Siamese Graph Neural Network for Link PredictionCode0
DeeperGCN: All You Need to Train Deeper GCNsCode0
Graph Neural Networks for Carbon Dioxide Adsorption Prediction in Aluminium-Exchanged ZeolitesCode0
Implicit Geometry and Interaction Embeddings Improve Few-Shot Molecular Property PredictionCode0
Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation LearningCode0
DYMAG: Rethinking Message Passing Using Dynamical-systems-based WaveformsCode0
Transformers for molecular property prediction: Lessons learned from the past five yearsCode0
Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property PredictionCode0
Transformers for molecular property prediction: Domain adaptation efficiently improves performanceCode0
Speak It Out: Solving Symbol-Related Problems with Symbol-to-Language Conversion for Language ModelsCode0
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