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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 201–250 of 691 papers

TitleStatusHype
GEOM: Energy-annotated molecular conformations for property prediction and molecular generationCode1
Optimal Transport Graph Neural NetworksCode1
Uncertainty Quantification Using Neural Networks for Molecular Property PredictionCode1
Global Attention based Graph Convolutional Neural Networks for Improved Materials Property PredictionCode1
Molecule Attention TransformerCode1
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information MaximizationCode1
Strategies for Pre-training Graph Neural NetworksCode1
Neural Message Passing for Quantum ChemistryCode1
Heat Kernel Goes Topological—0
Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures—0
Combining Graph Neural Networks and Mixed Integer Linear Programming for Molecular Inference under the Two-Layered Model—0
TRIDENT: Tri-Modal Molecular Representation Learning with Taxonomic Annotations and Local Correspondence—0
Large Language Model Agent for Modular Task Execution in Drug Discovery—0
A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools—0
Pix2Geomodel: A Next-Generation Reservoir Geomodeling with Property-to-Property Translation—0
CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation LearningCode0
GeoRecon: Graph-Level Representation Learning for 3D Molecules via Reconstruction-Based Pretraining—0
Information fusion strategy integrating pre-trained language model and contrastive learning for materials knowledge mining—0
Robust Molecular Property Prediction via Densifying Scarce Labeled DataCode0
Breaking Bad Molecules: Are MLLMs Ready for Structure-Level Molecular Detoxification?—0
BioLangFusion: Multimodal Fusion of DNA, mRNA, and Protein Language Models—0
DualEquiNet: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules—0
The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine LearningCode0
Graph Neural Networks in Modern AI-aided Drug Discovery—0
Positional Encoding meets Persistent Homology on GraphsCode0
Unlocking Chemical Insights: Superior Molecular Representations from Intermediate Encoder LayersCode0
Recent Developments in GNNs for Drug Discovery—0
Graph Positional Autoencoders as Self-supervised Learners—0
GenIC: An LLM-Based Framework for Instance Completion in Knowledge GraphsCode0
Iterative Corpus Refinement for Materials Property Prediction Based on Scientific Texts—0
Message-Passing State-Space Models: Improving Graph Learning with Modern Sequence Modeling—0
AdaptMol: Adaptive Fusion from Sequence String to Topological Structure for Few-shot Drug Discovery—0
All You Need Is Synthetic Task Augmentation—0
MolTextNet: A Two-Million Molecule-Text Dataset for Multimodal Molecular Learning—0
Pure Component Property Estimation Framework Using Explainable Machine Learning Methods—0
Quotient Complex Transformer (QCformer) for Perovskite Data Analysis—0
Impact of SMILES Notational Inconsistencies on Chemical Language Model PerformanceCode0
Soft causal learning for generalized molecule property prediction: An environment perspective—0
Multi-modal cascade feature transfer for polymer property prediction—0
34 Examples of LLM Applications in Materials Science and Chemistry: Towards Automation, Assistants, Agents, and Accelerated Scientific Discovery—0
BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models—0
SA-GAT-SR: Self-Adaptable Graph Attention Networks with Symbolic Regression for high-fidelity material property predictionCode0
MatMMFuse: Multi-Modal Fusion model for Material Property PredictionCode0
Sparse mixed linear modeling with anchor-based guidance for high-entropy alloy discovery—0
Towards Faster and More Compact Foundation Models for Molecular Property PredictionCode0
Learning Hierarchical Interaction for Accurate Molecular Property PredictionCode0
Supervised Pretraining for Material Property Prediction—0
Synergistic Benefits of Joint Molecule Generation and Property Prediction—0
Generative Deep Learning Framework for Inverse Design of Fuels—0
Leveraging Deep Operator Networks (DeepONet) for Acoustic Full Waveform Inversion (FWI)—0
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