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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 276–300 of 691 papers

TitleStatusHype
Molecular Graph Representation Learning via Structural Similarity InformationCode0
BayesGrad: Explaining Predictions of Graph Convolutional NetworksCode0
Domain-Adversarial Multi-Task Framework for Novel Therapeutic Property Prediction of CompoundsCode0
Do Graph Neural Networks Work for High Entropy Alloys?Code0
BatmanNet: Bi-branch Masked Graph Transformer Autoencoder for Molecular RepresentationCode0
Molecular geometric deep learningCode0
Diverse Explanations From Data-Driven and Domain-Driven Perspectives in the Physical SciencesCode0
MolCap-Arena: A Comprehensive Captioning Benchmark on Language-Enhanced Molecular Property PredictionCode0
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
Materials property prediction using symmetry-labeled graphs as atomic-position independent descriptorsCode0
Leveraging large language models for nano synthesis mechanism explanation: solid foundations or mere conjectures?Code0
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
Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation LearningCode0
DYMAG: Rethinking Message Passing Using Dynamical-systems-based WaveformsCode0
Data-Efficient Molecular Generation with Hierarchical Textual InversionCode0
Data-Driven Self-Supervised Graph Representation LearningCode0
Learning Hierarchical Interaction for Accurate Molecular Property PredictionCode0
Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property PredictionCode0
Graph Neural Networks for Surfactant Multi-Property PredictionCode0
Cuvis.Ai: An Open-Source, Low-Code Software Ecosystem for Hyperspectral Processing and ClassificationCode0
Interpreting the Syntactic and Social Elements of the Tweet Representations via Elementary Property Prediction TasksCode0
D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation LearningCode0
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