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ULaMDyn: Enhancing Excited-State Dynamics Analysis Through Streamlined Unsupervised Learning

Max Pinheiro Jr., Matheus O. Bispo, Rafael S. Mattos, Mariana Telles do Casal, Bidhan Chandra Garain, Josene M. Toldo, Saikat Mukherjee, Mario Barbatti

Version 1 posted 21 October 2024

172

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Analytical Chemistry

Working Paper

A Database Framework for Rapid Screening of Structure-Function Relationships in PFAS Chemistry

An Su, Krishna Rajan

Version 1 posted 01 July 2020

402

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Theoretical and Computational Chemistry

Working Paper

Learning Continuous and Data-Driven Molecular Descriptors by Translating Equivalent Chemical Representations

Robin Winter, Floriane Montanari, Frank Noé, Djork-Arné Clevert

Version 1 posted 30 July 2018

1,597

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Biological and Medicinal Chemistry

Working Paper

Towards uncoding hepatotoxicity of approved drugs through navigation of multiverse and consensus chemical spaces

Edgar López-López, José L. Medina-Franco

Version 1 posted 18 October 2022

163

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Polymer Science

Working Paper

Sequence Patterning, Topology, and Morphology in Single-chain Nanoparticles: Insights from Graph Theory and Machine Learning

Roshan Patel, Sophia Colmenares, Michael Webb

Version 2 posted 25 April 2023

380

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Theoretical and Computational Chemistry

Working Paper

The “Carbonyl-Lock” Mechanism Underlying Non-Aromatic Fluorescence in Biological Matter

Gonzalo Díaz Mirón, Jonathan A. Semelak, Luca Grisanti, Alex Rodriguez, Irene Conti, Martina Stella, Nicola Seriani, Nađa Došlić, Ivan Rivalta, Marco Garavelli, Dario A. Estrin, Gabriele S. Kaminski Schierle, Mariano C. González Lebrero, Ali Hassanali, Uriel N. Morzan

Version 1 posted 18 January 2023

335

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1

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Physical Chemistry

Working Paper

Improving machine learning performance on small chemical reaction data with unsupervised contrastive pretraining

Mingjian Wen, Samuel M. Blau, Xiaowei Xie, Shyam Dwaraknath, Kristin A. Persson

Version 2 posted 11 January 2022

731

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Materials Chemistry

Working Paper

Multiscale reactive model for 1,3,5-triamino-2,4,6-trinitrobenzene inferred by reactive MD simulations and unsupervised learning

Paul Lafourcade, Jean-Bernard Maillet, Jérôme Roche, Michael Sakano, Brenden Hamilton, Alejandro Strachan

Version 1 posted 14 June 2023

135

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Theoretical and Computational Chemistry

Working Paper

Molecular dynamics simulations of asphaltene aggregation: machine learning identification of representative molecules, polydispersity and inhibitor performance

Rémi Pétuya, Abhishek Punase, Emanuele Bosoni, Antonio Pedro de Oliveira Filho, Juan Sarria, Nirumpam Purkayastha, Jonathan Wylde, Stephan Mohr

Version 1 posted 02 November 2022

298

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Theoretical and Computational Chemistry

Working Paper

Unsupervised machine learning leads to an abiotic picomolar peptide ligand

Joseph S. Brown, Somesh Mohapatra, Michael A. Lee, Roman Misteli, Yitong Tseo, Nathalie M. Grob, Anthony J. Quartararo, Andrei Loas, Rafael Gomez-Bombarelli, Bradley L. Pentelute

Version 1 posted 24 May 2023

1,107

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11 results in Unsupervised learning in Keywords: Unsupervised learning

ULaMDyn: Enhancing Excited-State Dynamics Analysis Through Streamlined Unsupervised Learning

A Database Framework for Rapid Screening of Structure-Function Relationships in PFAS Chemistry

Learning Continuous and Data-Driven Molecular Descriptors by Translating Equivalent Chemical Representations

Towards uncoding hepatotoxicity of approved drugs through navigation of multiverse and consensus chemical spaces

Sequence Patterning, Topology, and Morphology in Single-chain Nanoparticles: Insights from Graph Theory and Machine Learning

The “Carbonyl-Lock” Mechanism Underlying Non-Aromatic Fluorescence in Biological Matter

Improving machine learning performance on small chemical reaction data with unsupervised contrastive pretraining

Multiscale reactive model for 1,3,5-triamino-2,4,6-trinitrobenzene inferred by reactive MD simulations and unsupervised learning

Molecular dynamics simulations of asphaltene aggregation: machine learning identification of representative molecules, polydispersity and inhibitor performance

Unsupervised machine learning leads to an abiotic picomolar peptide ligand

11 results in Keywords: Unsupervised learning