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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 626–650 of 691 papers

TitleStatusHype
Regression with Large Language Models for Materials and Molecular Property Prediction—0
Representing Molecules as Random Walks Over Interpretable Grammars—0
Reprogramming Pretrained Language Models for Protein Sequence Representation Learning—0
Revisiting Graph Neural Networks on Graph-level Tasks: Comprehensive Experiments, Analysis, and Improvements—0
RNACG: A Universal RNA Sequence Conditional Generation model based on Flow-Matching—0
Robust Subjective Visual Property Prediction from Crowdsourced Pairwise Labels—0
Improved Uncertainty Estimation of Graph Neural Network Potentials Using Engineered Latent Space Distances—0
Rxn Hypergraph: a Hypergraph Attention Model for Chemical Reaction Representation—0
Scaffold Splits Overestimate Virtual Screening Performance—0
Scalable Multi-Task Transfer Learning for Molecular Property Prediction—0
SE(3)-Invariant Multiparameter Persistent Homology for Chiral-Sensitive Molecular Property Prediction—0
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction—0
Self-supervised Learning and Graph Classification under Heterophily—0
Self-supervised learning for crystal property prediction via denoising—0
SeqProFT: Applying LoRA Finetuning for Sequence-only Protein Property Predictions—0
Set-based Meta-Interpolation for Few-Task Meta-Learning—0
Set-based Neural Network Encoding Without Weight Tying—0
Sheaf HyperNetworks for Personalized Federated Learning—0
Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond—0
Simplicial Message Passing for Chemical Property Prediction—0
Site-specific graph neural network for predicting protonation energy of oxygenate molecules—0
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method—0
SMILES-Mamba: Chemical Mamba Foundation Models for Drug ADMET Prediction—0
Smirk: An Atomically Complete Tokenizer for Molecular Foundation Models—0
Soft causal learning for generalized molecule property prediction: An environment perspective—0
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