SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 501–525 of 691 papers

TitleStatusHype
Knowledge graph-enhanced molecular contrastive learning with functional prompt—0
MolKD: Distilling Cross-Modal Knowledge in Chemical Reactions for Molecular Property Prediction—0
3D Molecular Geometry Analysis with 2D Graphs—0
Towards Unified AI Drug Discovery with Multiple Knowledge Modalities—0
Equivariant Parameter Sharing for Porous Crystalline MaterialsCode0
A Comprehensive and Versatile Multimodal Deep Learning Approach for Predicting Diverse Properties of Advanced Materials—0
HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations—0
Geometric Deep Learning for Molecular Crystal Structure Prediction—0
QUBO-inspired Molecular Fingerprint for Chemical Property Prediction—0
Molecular Property Prediction by Semantic-invariant Contrastive Learning—0
DR-Label: Improving GNN Models for Catalysis Systems by Label Deconstruction and ReconstructionCode0
Deep Learning Methods for Small Molecule Drug Discovery: A Survey—0
Hybrid machine-learned homogenization: Bayesian data mining and convolutional neural networks—0
Likelihood Annealing: Fast Calibrated Uncertainty for Regression—0
Graph Neural Networks Go Forward-Forward—0
An Investigation into Pre-Training Object-Centric Representations for Reinforcement Learning—0
GCI: A (G)raph (C)oncept (I)nterpretation FrameworkCode0
Implicit Geometry and Interaction Embeddings Improve Few-Shot Molecular Property PredictionCode0
Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction—0
Equivariant Message Passing Neural Network for Crystal Material DiscoveryCode0
Complete Neural Networks for Complete Euclidean Graphs—0
Outlier-Based Domain of Applicability Identification for Materials Property Prediction ModelsCode0
Reprogramming Pretrained Language Models for Protein Sequence Representation Learning—0
MolCPT: Molecule Continuous Prompt Tuning to Generalize Molecular Representation Learning—0
Material Property Prediction using Graphs based on Generically Complete Isometry Invariants—0
Show:102550
← PrevPage 21 of 28Next →

No leaderboard results yet.