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 301–350 of 691 papers

TitleStatusHype
Multi-channel learning for integrating structural hierarchies into context-dependent molecular representationCode1
Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural NetworksCode0
An algorithmic framework for synthetic cost-aware decision making in molecular designCode1
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method—0
Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go Indifferent—0
Sliceformer: Make Multi-head Attention as Simple as Sorting in Discriminative TasksCode0
Unsupervised Learning of Molecular Embeddings for Enhanced Clustering and Emergent Properties for Chemical Compounds—0
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property PredictionCode1
UniMAP: Universal SMILES-Graph Representation LearningCode1
LLM-Prop: Predicting Physical And Electronic Properties Of Crystalline Solids From Their Text DescriptionsCode1
Improving Molecular Properties Prediction Through Latent Space FusionCode2
Conformal Drug Property Prediction with Density Estimation under Covariate Shift—0
Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction—0
In-Context Learning for Few-Shot Molecular Property Prediction—0
Splicing Up Your Predictions with RNA Contrastive LearningCode0
Atom-Motif Contrastive Transformer for Molecular Property Prediction—0
ADMEOOD: Out-of-Distribution Benchmark for Drug Property Prediction—0
Lo-Hi: Practical ML Drug Discovery BenchmarkCode1
On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions—0
PointGAT: A quantum chemical property prediction model integrating graph attention and 3D geometry—0
Fragment-based Pretraining and Finetuning on Molecular GraphsCode1
Molecule Design by Latent Prompt Transformer—0
Towards out-of-distribution generalizable predictions of chemical kinetics propertiesCode0
AstroCLIP: A Cross-Modal Foundation Model for GalaxiesCode1
On the Stability of Expressive Positional Encodings for GraphsCode1
SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-trainingCode1
PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property PredictionCode0
ADMET property prediction through combinations of molecular fingerprintsCode1
3D-Mol: A Novel Contrastive Learning Framework for Molecular Property Prediction with 3D Information—0
Language models in molecular discovery—0
MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural NetworkCode2
Temporal graph models fail to capture global temporal dynamicsCode0
GPT-MolBERTa: GPT Molecular Features Language Model for molecular property prediction—0
DYMAG: Rethinking Message Passing Using Dynamical-systems-based WaveformsCode0
Motif-aware Attribute Masking for Molecular Graph Pre-trainingCode0
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation—0
Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property PredictionCode1
Geometry-aware Line Graph Transformer Pre-training for Molecular Property Prediction—0
Materials Informatics Transformer: A Language Model for Interpretable Materials Properties PredictionCode1
PeptideBERT: A Language Model based on Transformers for Peptide Property PredictionCode1
TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational GraphsCode1
Synergistic Fusion of Graph and Transformer Features for Enhanced Molecular Property Prediction—0
May the Force be with You: Unified Force-Centric Pre-Training for 3D Molecular Conformations—0
On Data Imbalance in Molecular Property Prediction with Pre-training—0
Is Self-Supervised Pretraining Good for Extrapolation in Molecular Property Prediction?—0
GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and TextCode1
Evaluating the diversity and utility of materials proposed by generative models—0
Fluid Viscosity Prediction Leveraging Computer Vision and Robot InteractionCode0
ChatMOF: An Autonomous AI System for Predicting and Generating Metal-Organic Frameworks—0
Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point CloudsCode0
Show:102550
← PrevPage 7 of 14Next →

No leaderboard results yet.