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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 51–75 of 691 papers

TitleStatusHype
TxGemma: Efficient and Agentic LLMs for Therapeutics—0
MLPROP -- an open interactive web interface for thermophysical property prediction with machine learning—0
CrystalFormer-RL: Reinforcement Fine-Tuning for Materials DesignCode2
Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification—0
Multimodal machine learning with large language embedding model for polymer property predictionCode0
AugWard: Augmentation-Aware Representation Learning for Accurate Graph ClassificationCode0
Symmetry-Informed Graph Neural Networks for Carbon Dioxide Isotherm and Adsorption Prediction in Aluminum-Substituted Zeolites—0
Discriminative protein sequence modelling with Latent Space Diffusion—0
Predicting performance-related properties of refrigerant based on tailored small-molecule functional group contribution—0
Machine Learning - Driven Materials Discovery: Unlocking Next-Generation Functional Materials -- A minireview—0
Chem42: a Family of chemical Language Models for Target-aware Ligand Generation—0
Lyra: An Efficient and Expressive Subquadratic Architecture for Modeling Biological Sequences—0
MetaFAP: Meta-Learning for Frequency Agnostic Prediction of Metasurface Properties—0
Ensemble Knowledge Distillation for Machine Learning Interatomic Potentials—0
A Materials Map Integrating Experimental and Computational Data via Graph-Based Machine Learning for Enhanced Materials Discovery—0
A Generalist Cross-Domain Molecular Learning Framework for Structure-Based Drug Discovery—0
Transformers for molecular property prediction: Domain adaptation efficiently improves performanceCode0
CrystalFramer: Rethinking the Role of Frames for SE(3)-Invariant Crystal Structure Modeling—0
Wyckoff Transformer: Generation of Symmetric CrystalsCode1
Integrating Predictive and Generative Capabilities by Latent Space Design via the DKL-VAE ModelCode0
InversionGNN: A Dual Path Network for Multi-Property Molecular OptimizationCode1
QCS-ADME: Quantum Circuit Search for Drug Property Prediction with Imbalanced Data and Regression Adaptation—0
LLM-Fusion: A Novel Multimodal Fusion Model for Accelerated Material Discovery—0
Integrating convolutional layers and biformer network with forward-forward and backpropagation trainingCode0
ChatMol: A Versatile Molecule Designer Based on the Numerically Enhanced Large Language Model—0
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