Cover Image

Combining Graph Neural Networks and Mixed Integer Linear Programming for Molecular Inference under the Two-Layered Model

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhu, Jianshen, Azam, Naveed Ahmed, Haraguchi, Kazuya, Zhao, Liang, Akutsu, Tatsuya
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Chemical Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Towards Environment-Sensitive Molecular Inference via Mixed Integer Linear Programming
by: Zhu, Jianshen, et al.
Published: (2025)

Mixing Vector Model for Copolymer Inference via Mixed Integer Linear Programming
by: Zhu, Jianshen, et al.
Published: (2026)

Cycle-Configuration: A Novel Graph-theoretic Descriptor Set for Molecular Inference
by: Song, Bowen, et al.
Published: (2024)

A Unified Approach to Inferring Chemical Compounds with the Desired Aqueous Solubility
by: Batool, Muniba, et al.
Published: (2024)

Finding Thermodynamically Favorable Pathways in Chemical Reaction Networks Using Flows in Hypergraphs and Mixed-Integer Linear Programming
by: Pal, Adittya, et al.
Published: (2024)

A Non Linear Spectral Graph Neural Network Simulator for More Stable and Accurate Rollouts
by: Salman, Salman N., et al.
Published: (2026)

Impact of Local Descriptors Derived from Machine Learning Potentials in Graph Neural Networks for Molecular Property Prediction
by: Uchiyama, Ryoichi, et al.
Published: (2026)

A Graph Neural Network-Based Approach to XANES Data Analysis
by: Zhan, Fei, et al.
Published: (2022)

NeuralTSNE: A Python Package for the Dimensionality Reduction of Molecular Dynamics Data Using Neural Networks
by: Tajs, Patryk, et al.
Published: (2025)

A Comprehensive Survey of Linear, Integer, and Mixed-Integer Programming Approaches for Optimizing Resource Allocation in 5G and Beyond Networks
by: Ejaz, Naveed, et al.
Published: (2025)

MixPI: Mixed-Time Slicing Path Integral Software for Quantized Molecular Dynamics Simulations
by: Johnson, Britta A., et al.
Published: (2024)

Efficient Implementation of Relativistic Coupled Cluster Linear Response Theory in Combination with Perturbation Sensitive Natural Spinors and Cholesky Decomposition Treatment of Two-electron Integrals
by: Chakraborty, Sudipta, et al.
Published: (2026)

A Neural-Network-Based Selective Configuration Interaction Approach to Molecular Electronic Structure
by: Schmerwitz, Yorick L. A., et al.
Published: (2024)

Neural Network Approach for Predicting Infrared Spectra from 3D Molecular Structure
by: Al, Saleh Abdul, et al.
Published: (2024)

Neural Network Based Molecular Structure Retrieval from Coulomb Explosion Imaging Data
by: Ghanaatian, Amirhossein, et al.
Published: (2026)

Molecular dynamics simulation with finite electric fields using Perturbed Neural Network Potentials
by: Joll, Kit, et al.
Published: (2024)

Systematic evaluation of the isolated effect of tissue environment on the transcriptome using a single-cell RNA-seq atlas dataset
by: Okada, Daigo, et al.
Published: (2024)

FragNet: A Graph Neural Network for Molecular Property Prediction with Four Levels of Interpretability
by: Panapitiya, Gihan, et al.
Published: (2024)

Uniaxial Ordering by Self-Assembly of Isotropic Octahedral Junctions
by: Saito, Kazuya
Published: (2025)

The Importance of Layer-Dependent Molecular Twisting for the Structural Anisotropy of Interfacial Water
by: Fellows, Alexander P., et al.
Published: (2025)

Combining Molecular Dynamics and Experimental Methods for the Parametrization of Binary Carbonate-Based Electrolytes
by: Lehnert, Lukas, et al.
Published: (2025)

Accelerating Molecular Dynamics Simulations with Foundation Neural Network Models using Multiple Time-Step and Distillation
by: Cattin, Côme, et al.
Published: (2025)

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

Molecular Polarizability under Vibrational Strong Coupling
by: Schnappinger, Thomas, et al.
Published: (2025)

Polarizable Water Model with Ab Initio Neural Network Dynamic Charges and Spontaneous Charge Transfer
by: Liang, Qiujiang, et al.
Published: (2024)

Graph Neural Networks for Surfactant Multi-Property Prediction
by: Brozos, Christoforos, et al.
Published: (2024)

The Molecular Mechanism of Resveratrol in the Treatment of Chronic Rhinosinusitis Through a Combination of Network Pharmacology and In Vitro Validation
by: Xiao Cheng, et al.
Published: (2025)

Analysis of Atom-level pretraining with Quantum Mechanics (QM) data for Graph Neural Networks Molecular property models
by: Arjona-Medina, Jose, et al.
Published: (2024)

Explicit, Machine-Learned Two-Body Potentials for Molecular Simulations
by: Chaton, Kham Lek, et al.
Published: (2026)

Semiclassical Nonadiabatic Molecular Dynamics Using Linearized Pair-Density Functional Theory
by: Hennefarth, Matthew R., et al.
Published: (2024)

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

Meta-Learning Linear Models for Molecular Property Prediction
by: Pimonova, Yulia, et al.
Published: (2025)

Efficient Parallelization of Message Passing Neural Network Potentials for Large-scale Molecular Dynamics
by: Xia, Junfan, et al.
Published: (2025)

The Bigger the Better? Accurate Molecular Potential Energy Surfaces from Minimalist Neural Networks
by: Käser, Silvan, et al.
Published: (2024)

QMCTorch: Molecular Wavefunctions with Neural Components for Energy and Force Calculations
by: Renaud, Nicolas
Published: (2025)

Predicting the Temperature Dependence of Surfactant CMCs Using Graph Neural Networks
by: Brozos, Christoforos, et al.
Published: (2024)

Predicting the Temperature-Dependent CMC of Surfactant Mixtures with Graph Neural Networks
by: Brozos, Christoforos, et al.
Published: (2024)

Mo Atom Rearrangement Drives Layer-Dependent Reactivity in Two-Dimensional MoS2
by: Wang, Zifan, et al.
Published: (2025)

Scaling Graph Neural Networks to Large Proteins
by: Airas, Justin, et al.
Published: (2024)

Advancing Molecular Machine Learning Representations with Stereoelectronics-Infused Molecular Graphs
by: Boiko, Daniil A., et al.
Published: (2024)