Cover Image

Neural Graph Matching Improves Retrieval Augmented Generation in Molecular Machine Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Runzhong, Wang, Rui-Xi, Manjrekar, Mrunali, Coley, Connor W.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Quantitative Methods
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra
by: Bohde, Montgomery, et al.
Published: (2025)

FRIGID: Scaling Diffusion-Based Molecular Generation from Mass Spectra at Training and Inference Time
by: Bohde, Montgomery, et al.
Published: (2026)

Generative structural elucidation from mass spectra as an iterative optimization problem
by: Manjrekar, Mrunali, et al.
Published: (2026)

A Genetic Algorithm for Navigating Synthesizable Molecular Spaces
by: Lo, Alston, et al.
Published: (2025)

Generating Molecular Fragmentation Graphs with Autoregressive Neural Networks
by: Goldman, Samuel, et al.
Published: (2023)

Anticipating the Selectivity of Intramolecular Cyclization Reaction Pathways with Neural Network Potentials
by: Casetti, Nicholas, et al.
Published: (2025)

KA-GNN: Kolmogorov-Arnold Graph Neural Networks for Molecular Property Prediction
by: Li, Longlong, et al.
Published: (2024)

Flow-Matching Based Refiner for Molecular Conformer Generation
by: Xu, Xiangyang, et al.
Published: (2025)

Forecasting Antimicrobial Resistance Trends Using Machine Learning on WHO GLASS Surveillance Data: A Retrieval-Augmented Generation Approach for Policy Decision Support
by: Turja, Md Tanvir Hasan
Published: (2026)

ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation
by: Hassan, Majdi, et al.
Published: (2024)

SubGDiff: A Subgraph Diffusion Model to Improve Molecular Representation Learning
by: Zhang, Jiying, et al.
Published: (2024)

Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search
by: Yu, Kevin, et al.
Published: (2024)

MolGuidance: Advanced Guidance Strategies for Conditional Molecular Generation with Flow Matching
by: Jin, Jirui, et al.
Published: (2025)

Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel
by: Li, Xuan, et al.
Published: (2023)

Predicting Biomedical Interactions with Probabilistic Model Selection for Graph Neural Networks
by: KC, Kishan, et al.
Published: (2022)

Enhancing Drug Discovery: Autoencoder-Based Latent Space Augmentation for Improved Molecular Solubility Prediction using LatMixSol
by: Hasankhani, Mohammad Saleh
Published: (2025)

ProteinZero: Self-Improving Protein Generation via Online Reinforcement Learning
by: Wang, Ziwen, et al.
Published: (2025)

Molecular Odor Prediction Based on Multi-Feature Graph Attention Networks
by: Xie, HongXin, et al.
Published: (2025)

Graph Fourier Neural ODEs: Modeling Spatial-temporal Multi-scales in Molecular Dynamics
by: Sun, Fang, et al.
Published: (2024)

Efficient and Robust Continual Graph Learning for Graph Classification in Biology
by: Zhang, Ding, et al.
Published: (2024)

Predicting Drug Solubility Using Different Machine Learning Methods -- Linear Regression Model with Extracted Chemical Features vs Graph Convolutional Neural Network
by: Ho, John, et al.
Published: (2023)

Molecular Topological Profile (MOLTOP) -- Simple and Strong Baseline for Molecular Graph Classification
by: Adamczyk, Jakub, et al.
Published: (2024)

How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval
by: Fradkin, Philip, et al.
Published: (2024)

Graph-Theoretic Models for the Prediction of Molecular Measurements
by: Niane, Anna, et al.
Published: (2026)

Batched Bayesian optimization by maximizing the probability of including the optimum
by: Fromer, Jenna, et al.
Published: (2024)

An algorithmic framework for synthetic cost-aware decision making in molecular design
by: Fromer, Jenna C., et al.
Published: (2023)

SGAC: A Graph Neural Network Framework for Imbalanced and Structure-Aware AMP Classification
by: Wang, Yingxu, et al.
Published: (2024)

Graph Residual based Method for Molecular Property Prediction
by: Sen, Kanad, et al.
Published: (2024)

HiGraphDTI: Hierarchical Graph Representation Learning for Drug-Target Interaction Prediction
by: Liu, Bin, et al.
Published: (2024)

Motif-aware Attribute Masking for Molecular Graph Pre-training
by: Inae, Eric, et al.
Published: (2023)

CAGenMol: Condition-Aware Diffusion Language Model for Goal-Directed Molecular Generation
by: Li, Yanting, et al.
Published: (2026)

A Universal Non-Parametric Approach For Improved Molecular Sequence Analysis
by: Ali, Sarwan, et al.
Published: (2024)

Distribution Learning for Molecular Regression
by: Shoghi, Nima, et al.
Published: (2024)

XIMP: Cross Graph Inter-Message Passing for Molecular Property Prediction
by: Ehrlich, Anatol, et al.
Published: (2026)

Out-of-Distribution Detection in Molecular Complexes via Diffusion Models for Irregular Graphs
by: Graber, David, et al.
Published: (2025)

Active Learning on Synthons for Molecular Design
by: Grigg, Tom George, et al.
Published: (2025)

Learning Molecular Representation in a Cell
by: Liu, Gang, et al.
Published: (2024)

Curriculum-Augmented GFlowNets For mRNA Sequence Generation
by: Laajil, Aya, et al.
Published: (2025)

Learning to Extend Molecular Scaffolds with Structural Motifs
by: Maziarz, Krzysztof, et al.
Published: (2021)

Comparative Analysis of Data Preprocessing Methods, Feature Selection Techniques and Machine Learning Models for Improved Classification and Regression Performance on Imbalanced Genetic Data
by: Kaur, Arshmeet, et al.
Published: (2024)