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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 251–300 of 691 papers

TitleStatusHype
Enhancing Molecular Property Prediction with Auxiliary Learning and Task-Specific AdaptationCode0
Enhancing Molecular Property Prediction via Mixture of Collaborative ExpertsCode0
Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide PropertiesCode0
Adapting Differential Molecular Representation with Hierarchical Prompts for Multi-label Property PredictionCode0
PatchProt: Hydrophobic patch prediction using protein foundation modelsCode0
Structure-based out-of-distribution (OOD) materials property prediction: a benchmark studyCode0
MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property PredictionCode0
MUBen: Benchmarking the Uncertainty of Molecular Representation ModelsCode0
Embedding Graphs on Grassmann ManifoldCode0
MolXPT: Wrapping Molecules with Text for Generative Pre-trainingCode0
Motif-aware Attribute Masking for Molecular Graph Pre-trainingCode0
MolMetaLM: a Physicochemical Knowledge-Guided Molecular Meta Language ModelCode0
Efficient Chemical Space Exploration Using Active Learning Based on Marginalized Graph Kernel: an Application for Predicting the Thermodynamic Properties of Alkanes with Molecular SimulationCode0
MolPLA: A Molecular Pretraining Framework for Learning Cores, R-Groups and their Linker JointsCode0
Multimodal machine learning with large language embedding model for polymer property predictionCode0
Efficient Approximations of Complete Interatomic Potentials for Crystal Property PredictionCode0
Molecule Property Prediction and Classification with Graph HypernetworksCode0
Molecule Property Prediction Based on Spatial Graph EmbeddingCode0
MoleculeCLA: Rethinking Molecular Benchmark via Computational Ligand-Target Binding AnalysisCode0
Molecular Property Prediction: A Multilevel Quantum Interactions Modeling PerspectiveCode0
Multimodal Model with Text and Drug Embeddings for Adverse Drug Reaction ClassificationCode0
Molecular Graph Contrastive Learning with Line GraphCode0
Molecular Graph Representation Learning Integrating Large Language Models with Domain-specific Small ModelsCode0
DScribe: Library of Descriptors for Machine Learning in Materials ScienceCode0
DR-Label: Improving GNN Models for Catalysis Systems by Label Deconstruction and ReconstructionCode0
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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