# A Method for Inferring Polymers Based on Linear Regression and Integer Programming

arXiv: https://arxiv.org/abs/2109.02628 · HTML: https://mlsanity.com/paper/2109.02628/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 37 references that are in the map.
- First posted on arXiv 24 Aug 2021.

## Builds on (most cited first, 9 of 9)

- [Semi-Supervised Classification with Graph Convolutional Networks](https://mlsanity.com/paper/1609.02907/) (2016)
- [Automatic chemical design using a data-driven continuous representation of molecules](https://mlsanity.com/paper/1610.02415/) (2016)
- [MolGAN: An implicit generative model for small molecular graphs](https://mlsanity.com/paper/1805.11973/) (2018)
- [GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation](https://mlsanity.com/paper/2001.09382/) (2020)
- [Grammar Variational Autoencoder](https://mlsanity.com/paper/1703.01925/) (2017)
- [GraphNVP: An Invertible Flow Model for Generating Molecular Graphs](https://mlsanity.com/paper/1905.11600/) (2019)
- [ChemTS: An Efficient Python Library for de novo Molecular Generation](https://mlsanity.com/paper/1710.00616/) (2017)
- [A Novel Method for Inference of Acyclic Chemical Compounds with Bounded Branch-height Based on Artificial Neural Networks and Integer Programming](https://mlsanity.com/paper/2009.09646/) (2020)
- [A novel method for inference of chemical compounds with prescribed topological substructures based on integer programming](https://mlsanity.com/paper/2010.09203/) (2020)

## Built on by (most cited first, 5 of 5)

- [Molecular Design Based on Integer Programming and Quadratic Descriptors in a Two-layered Model](https://mlsanity.com/paper/2209.13527/) (2022)
- [Molecular Design Based on Integer Programming and Splitting Data Sets by Hyperplanes](https://mlsanity.com/paper/2305.00801/) (2023)
- [Cycle-Configuration: A Novel Graph-theoretic Descriptor Set for Molecular Inference](https://mlsanity.com/paper/2408.05136/) (2024)
- [A Unified Approach to Inferring Chemical Compounds with the Desired Aqueous Solubility](https://mlsanity.com/paper/2409.04301/) (2024)
- [Mixing Vector Model for Copolymer Inference via Mixed Integer Linear Programming](https://mlsanity.com/paper/2605.29329/) (2026)

## Abstract (arXiv)

A novel framework has recently been proposed for designing the molecular structure of chemical compounds with a desired chemical property using both artificial neural networks and mixed integer linear programming. In this paper, we design a new method for inferring a polymer based on the framework. For this, we introduce a new way of representing a polymer as a form of monomer and define new descriptors that feature the structure of polymers. We also use linear regression as a building block of constructing a prediction function in the framework. The results of our computational experiments reveal a set of chemical properties on polymers to which a prediction function constructed with linear regression performs well. We also observe that the proposed method can infer polymers with up to 50 non-hydrogen atoms in a monomer form.