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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 301–350 of 691 papers

TitleStatusHype
Materials property prediction using symmetry-labeled graphs as atomic-position independent descriptorsCode0
Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property PredictionCode0
Adapting Differential Molecular Representation with Hierarchical Prompts for Multi-label Property PredictionCode0
Independent Vector Analysis for Data Fusion Prior to Molecular Property Prediction with Machine LearningCode0
Structure-Enhanced Meta-Learning For Few-Shot Graph ClassificationCode0
GenIC: An LLM-Based Framework for Instance Completion in Knowledge GraphsCode0
Positional Encoding meets Persistent Homology on GraphsCode0
GeomCLIP: Contrastive Geometry-Text Pre-training for MoleculesCode0
Subgraph Aggregation for Out-of-Distribution Generalization on GraphsCode0
AugWard: Augmentation-Aware Representation Learning for Accurate Graph ClassificationCode0
Diverse Explanations From Data-Driven and Domain-Driven Perspectives in the Physical SciencesCode0
Graph Neural Networks for Carbon Dioxide Adsorption Prediction in Aluminium-Exchanged ZeolitesCode0
GeoT: A Geometry-aware Transformer for Reliable Molecular Property Prediction and Chemically Interpretable Representation LearningCode0
PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property PredictionCode0
Surrogate- and invariance-boosted contrastive learning for data-scarce applications in scienceCode0
D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation LearningCode0
Uni-Mol: A Universal 3D Molecular Representation Learning FrameworkCode0
Large-Scale Knowledge Integration for Enhanced Molecular Property PredictionCode0
Unlocking Chemical Insights: Superior Molecular Representations from Intermediate Encoder LayersCode0
Tanimoto Random Features for Scalable Molecular Machine LearningCode0
Embedding Graphs on Grassmann ManifoldCode0
CL-MFAP: A Contrastive Learning-Based Multimodal Foundation Model for Molecular Property Prediction and Antibiotic ScreeningCode0
LiteGEM: Lite Geometry Enhanced Molecular Representation Learning for Quantum Property PredictionCode0
Cuvis.Ai: An Open-Source, Low-Code Software Ecosystem for Hyperspectral Processing and ClassificationCode0
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property PredictionCode0
Temporal graph models fail to capture global temporal dynamicsCode0
Unsupervised Musical Object Discovery from AudioCode0
testRNN: Coverage-guided Testing on Recurrent Neural NetworksCode0
Homomorphism Counts as Structural Encodings for Graph LearningCode0
Unveiling Molecular Secrets: An LLM-Augmented Linear Model for Explainable and Calibratable Molecular Property PredictionCode0
CoarsenConf: Equivariant Coarsening with Aggregated Attention for Molecular Conformer GenerationCode0
Establishing Deep InfoMax as an effective self-supervised learning methodology in materials informaticsCode0
Global Human-guided Counterfactual Explanations for Molecular Properties via Reinforcement LearningCode0
Text to Band Gap: Pre-trained Language Models as Encoders for Semiconductor Band Gap PredictionCode0
Coarse-Grained Configurational Polymer Fingerprints for Property Prediction using Machine LearningCode0
Do Graph Neural Networks Work for High Entropy Alloys?Code0
The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine LearningCode0
Domain-Adversarial Multi-Task Framework for Novel Therapeutic Property Prediction of CompoundsCode0
Interpretation of Semantic Tweet RepresentationsCode0
The Role of Model Architecture and Scale in Predicting Molecular Properties: Insights from Fine-Tuning RoBERTa, BART, and LLaMACode0
Data-Driven Self-Supervised Graph Representation LearningCode0
Graph Anisotropic DiffusionCode0
Ranking Structured Objects with Graph Neural NetworksCode0
ReactEmbed: A Cross-Domain Framework for Protein-Molecule Representation Learning via Biochemical Reaction NetworksCode0
Identifying Semantic Component for Robust Molecular Property PredictionCode0
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and ChemistryCode0
Data-Efficient Molecular Generation with Hierarchical Textual InversionCode0
Leveraging large language models for nano synthesis mechanism explanation: solid foundations or mere conjectures?Code0
Attentive Walk-Aggregating Graph Neural NetworksCode0
Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property PredictionCode0
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