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

Showing 131140 of 691 papers

TitleStatusHype
CrysMMNet: Multimodal Representation for Crystal Property PredictionCode1
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and moleculesCode1
Implicit Convolutional Kernels for Steerable CNNsCode1
CrysGNN : Distilling pre-trained knowledge to enhance property prediction for crystalline materialsCode1
AstroCLIP: A Cross-Modal Foundation Model for GalaxiesCode1
Hierarchical graph neural nets can capture long-range interactionsCode1
Deep learning-based denoising for fast time-resolved flame emission spectroscopy in high-pressure combustion environmentCode1
Directed Graph Grammars for Sequence-based LearningCode1
Assigning Confidence to Molecular Property PredictionCode1
Copolymer Informatics with Multi-Task Deep Neural NetworksCode1
Show:102550
← PrevPage 14 of 70Next →

No leaderboard results yet.