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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

Showing 281290 of 691 papers

TitleStatusHype
MolMetaLM: a Physicochemical Knowledge-Guided Molecular Meta Language ModelCode0
AugWard: Augmentation-Aware Representation Learning for Accurate Graph ClassificationCode0
An Empirical Study of Retrieval-enhanced Graph Neural NetworksCode0
A Large Encoder-Decoder Family of Foundation Models For Chemical LanguageCode0
Leveraging large language models for nano synthesis mechanism explanation: solid foundations or mere conjectures?Code0
Large-Scale Knowledge Integration for Enhanced Molecular Property PredictionCode0
DeeperGCN: All You Need to Train Deeper GCNsCode0
Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization ProblemsCode0
Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property PredictionCode0
Data-Efficient Molecular Generation with Hierarchical Textual InversionCode0
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