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molecular representation
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TRIDENT: Tri-Modal Molecular Representation Learning with Taxonomic Annotations and Local Correspondence
GeoRecon: Graph-Level Representation Learning for 3D Molecules via Reconstruction-Based Pretraining
AdaptMol: Adaptive Fusion from Sequence String to Topological Structure for Few-shot Drug Discovery
2DNMRGym: An Annotated Experimental Dataset for Atom-Level Molecular Representation Learning in 2D NMR via Surrogate Supervision
Pure Component Property Estimation Framework Using Explainable Machine Learning Methods
Multi-Modal Molecular Representation Learning via Structure Awareness
BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models
Synergistic Benefits of Joint Molecule Generation and Property Prediction
MolSpectra: Pre-training 3D Molecular Representation with Multi-modal Energy Spectra
UniMatch: Universal Matching from Atom to Task for Few-Shot Drug Discovery
Knowledge-aware contrastive heterogeneous molecular graph learning
FragmentNet: Adaptive Graph Fragmentation for Graph-to-Sequence Molecular Representation Learning
MolGraph-xLSTM: A graph-based dual-level xLSTM framework with multi-head mixture-of-experts for enhanced molecular representation and interpretability
Can Molecular Evolution Mechanism Enhance Molecular Representation?
Representation of Molecules via Algebraic Data Types : Advancing Beyond SMILES & SELFIES
GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation
GenMol: A Drug Discovery Generalist with Discrete Diffusion
MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights
SMI-Editor: Edit-based SMILES Language Model with Fragment-level Supervision
Tokenizing 3D Molecule Structure with Quantized Spherical Coordinates
BAPULM: Binding Affinity Prediction using Language Models
Chemical Language Model Linker: blending text and molecules with modular adapters
Multi-view biomedical foundation models for molecule-target and property prediction
MolMix: A Simple Yet Effective Baseline for Multimodal Molecular Representation Learning
E3STO: Orbital Inspired SE(3)-Equivariant Molecular Representation for Electron Density Prediction
FARM: Functional Group-Aware Representations for Small Molecules
FineMolTex: Towards Fine-grained Molecular Graph-Text Pre-training
Smirk: An Atomically Complete Tokenizer for Molecular Foundation Models
Molecular Graph Representation Learning via Structural Similarity Information
Mayer-homology learning prediction of protein-ligand binding affinities
Active Learning of Molecular Data for Task-Specific Objectives
Advancing Molecular Machine Learning Representations with Stereoelectronics-Infused Molecular Graphs
GNN-SKAN: Harnessing the Power of SwallowKAN to Advance Molecular Representation Learning with GNNs
Technical report: Improving the properties of molecules generated by LIMO
Improving Performance Prediction of Electrolyte Formulations with Transformer-based Molecular Representation Model
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