:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Dablander, Markus, Hanser, Thierry, Lambiotte, Renaud, Morris, Garrett M.
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Chemical Physics Biomolecules
Online Access:	https://arxiv.org/abs/2403.17954
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Expanding Chemical Representation with k-mers and Fragment-based Fingerprints for Molecular Fingerprinting
by: Ali, Sarwan, et al.
Published: (2024)

Investigating Graph Neural Networks and Classical Feature-Extraction Techniques in Activity-Cliff and Molecular Property Prediction
by: Dablander, Markus
Published: (2024)

E(3)-equivariant models cannot learn chirality: Field-based molecular generation
by: Dumitrescu, Alexandru, et al.
Published: (2024)

Superior Molecular Representations from Intermediate Encoder Layers
by: Pinto, Luis
Published: (2025)

Instruction-Based Molecular Graph Generation with Unified Text-Graph Diffusion Model
by: Xiang, Yuran, et al.
Published: (2024)

Uncertainty Quantification for Molecular Property Predictions with Graph Neural Architecture Search
by: Jiang, Shengli, et al.
Published: (2023)

EquiBoost: An Equivariant Boosting Approach to Molecular Conformation Generation
by: Yang, Yixuan, et al.
Published: (2025)

RGFN: Synthesizable Molecular Generation Using GFlowNets
by: Koziarski, Michał, et al.
Published: (2024)

Physics-informed generative model for drug-like molecule conformers
by: Williams, David C., et al.
Published: (2024)

GP-MoLFormer: A Foundation Model For Molecular Generation
by: Ross, Jerret, et al.
Published: (2024)

De Novo Molecular Design Enabled by Direct Preference Optimization and Curriculum Learning
by: Hou, Junyu
Published: (2025)

Pre-training of Molecular GNNs via Conditional Boltzmann Generator
by: Koge, Daiki, et al.
Published: (2023)

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction
by: Zhang, He, et al.
Published: (2024)

Understanding active learning of molecular docking and its applications
by: Kim, Jeonghyeon, et al.
Published: (2024)

HEroBM: a deep equivariant graph neural network for universal backmapping from coarse-grained to all-atom representations
by: Angioletti, Daniele, et al.
Published: (2024)

EquiFlow: Equivariant Conditional Flow Matching with Optimal Transport for 3D Molecular Conformation Prediction
by: Tian, Qingwen, et al.
Published: (2024)

GraphXForm: Graph transformer for computer-aided molecular design
by: Pirnay, Jonathan, et al.
Published: (2024)

MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights
by: Hu, Jingjing, et al.
Published: (2024)

Sculpting Molecules in Text-3D Space: A Flexible Substructure Aware Framework for Text-Oriented Molecular Optimization
by: Zhang, Kaiwei, et al.
Published: (2024)

Clever Hans in Chemistry: Chemist Style Signals Confound Activity Prediction on Public Benchmarks
by: Blevins, Andrew D., et al.
Published: (2025)

Distributional Priors Guided Diffusion for Generating 3D Molecules in Low Data Regimes
by: Hong, Haokai, et al.
Published: (2024)

A 3D pocket-aware and evolutionary conserved interaction guided diffusion model for molecular optimization
by: Qiao, Anjie, et al.
Published: (2025)

Guided Multi-objective Generative AI to Enhance Structure-based Drug Design
by: Kadan, Amit, et al.
Published: (2024)

Procedural Synthesis of Synthesizable Molecules
by: Sun, Michael, et al.
Published: (2024)

Look the Other Way: Designing 'Positive' Molecules with Negative Data via Task Arithmetic
by: Özçelik, Rıza, et al.
Published: (2025)

Training-Free Guidance for Discrete Diffusion Models for Molecular Generation
by: Kerby, Thomas J., et al.
Published: (2024)

Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning
by: Liu, Gang, et al.
Published: (2024)

E3STO: Orbital Inspired SE(3)-Equivariant Molecular Representation for Electron Density Prediction
by: Mitnikov, Ilan, et al.
Published: (2024)

EquiJump: Protein Dynamics Simulation via SO(3)-Equivariant Stochastic Interpolants
by: Costa, Allan dos Santos, et al.
Published: (2024)

NeuralPLexer3: Accurate Biomolecular Complex Structure Prediction with Flow Models
by: Qiao, Zhuoran, et al.
Published: (2024)

Transfer Learning across Different Chemical Domains: Virtual Screening of Organic Materials with Deep Learning Models Pretrained on Small Molecule and Chemical Reaction Data
by: Zhang, Chengwei, et al.
Published: (2023)

Leap: molecular synthesisability scoring with intermediates
by: Calvi, Antonia, et al.
Published: (2024)

Learning Collective Variables with Synthetic Data Augmentation through Physics-Inspired Geodesic Interpolation
by: Yang, Soojung, et al.
Published: (2024)

CREMP: Conformer-rotamer ensembles of macrocyclic peptides for machine learning
by: Grambow, Colin A., et al.
Published: (2023)

On Improving Graph Neural Networks for QSAR by Pre-training on Extended-Connectivity Fingerprints
by: Money-Kyrle, Sam, et al.
Published: (2026)

A Transformer Based Generative Chemical Language AI Model for Structural Elucidation of Organic Compounds
by: Tan, Xiaofeng
Published: (2024)

MultiModal-Learning for Predicting Molecular Properties: A Framework Based on Image and Graph Structures
by: Wang, Zhuoyuan, et al.
Published: (2023)

From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning
by: Min, Yaosen, et al.
Published: (2022)

A Novel 4-D Dataset Paradigm for Studying Complete Ligand-Protein Dissociation Dynamics
by: Li, Maodong, et al.
Published: (2025)

FreeCG: Free the Design Space of Clebsch-Gordan Transform for Machine Learning Force Fields
by: Shao, Shihao, et al.
Published: (2024)