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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 351–375 of 691 papers

TitleStatusHype
A Structured Framework for Predicting Sustainable Aviation Fuel Properties using Liquid-Phase FTIR and Machine Learning—0
LLM-Fusion: A Novel Multimodal Fusion Model for Accelerated Material Discovery—0
34 Examples of LLM Applications in Materials Science and Chemistry: Towards Automation, Assistants, Agents, and Accelerated Scientific Discovery—0
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation—0
3D Graph Contrastive Learning for Molecular Property Prediction—0
3D-Mol: A Novel Contrastive Learning Framework for Molecular Property Prediction with 3D Information—0
3D Molecular Geometry Analysis with 2D Graphs—0
3D Pre-training improves GNNs for Molecular Property Prediction—0
A 3D-Shape Similarity-based Contrastive Approach to Molecular Representation Learning—0
Accelerating Molecular Graph Neural Networks via Knowledge Distillation—0
A Comprehensive and Versatile Multimodal Deep Learning Approach for Predicting Diverse Properties of Advanced Materials—0
Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures—0
A Crystal-Specific Pre-Training Framework for Crystal Material Property Prediction—0
ADA-GNN: Atom-Distance-Angle Graph Neural Network for Crystal Material Property Prediction—0
Adaptive Invariance for Molecule Property Prediction—0
AdaptMol: Adaptive Fusion from Sequence String to Topological Structure for Few-shot Drug Discovery—0
Addressing Over-Smoothing in Graph Neural Networks via Deep Supervision—0
AdaMR: Adaptable Molecular Representation for Unified Pre-training Strategy—0
ADMEOOD: Out-of-Distribution Benchmark for Drug Property Prediction—0
Advancements in Molecular Property Prediction: A Survey of Single and Multimodal Approaches—0
Advancing Molecular Machine Learning Representations with Stereoelectronics-Infused Molecular Graphs—0
Affinity-Aware Graph Networks—0
A Generalist Cross-Domain Molecular Learning Framework for Structure-Based Drug Discovery—0
A Kriging-Random Forest Hybrid Model for Real-time Ground Property Prediction during Earth Pressure Balance Shield Tunneling—0
AlloyBERT: Alloy Property Prediction with Large Language Models—0
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