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Theoretical and Computational Chemistry

Working Paper

Transformer-CNN: Fast and Reliable Tool for QSAR

Pavel Karpov, Guillaume Godin, Igor Tetko

Version 1 posted 21 October 2019

926

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2

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Theoretical and Computational Chemistry

Working Paper

Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models

Chenru Duan, Jon Paul Janet, Fang Liu, Aditya Nandy, Heather Kulik

Version 1 posted 23 January 2019

1,372

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Theoretical and Computational Chemistry

Working Paper

Hidden Bias in the DUD-E Dataset Leads to Misleading Performance of Deep Learning in Structure-Based Virtual Screening

Lieyang Chen, Anthony Cruz, Steven Ramsey, Callum J. Dickson, José S. Duca, Viktor Hornak, David R. Koes, Tom Kurtzman

Version 1 posted 25 March 2019

1,378

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2

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Physical Chemistry

Working Paper

Towards the Atomic-Level Analysis of Ground-State Electronic Structures of Solid Materials via Prediction from Core-Loss Spectra

Izumi Takahara, Kiyou Shibata, Teruyasu Mizoguchi

Version 1 posted 02 May 2024

149

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Energy

Working Paper

High-Speed Cyclic Voltammetry Regressions Using Machine Learning

Darik Rosser, Kevin Leonard

Version 1 posted 14 January 2025

126

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Theoretical and Computational Chemistry

Working Paper

Learning RMSD to Improve Protein-Ligand Scoring and Pose Selection

Rishal Aggarwal, David R. Koes

Version 2 posted 03 March 2020

2,795

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5

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Nanoscience

Working Paper

A deep learning approach for quantum dots sizing from wide-angle X-ray scattering data

Lucia Allara, Federica Bertolotti, Antonietta Guagliardi

Version 1 posted 08 November 2023

197

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Refine Search

7 results in Convolutional Neural Networks in Keywords: Convolutional Neural Networks

Transformer-CNN: Fast and Reliable Tool for QSAR

Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models

Hidden Bias in the DUD-E Dataset Leads to Misleading Performance of Deep Learning in Structure-Based Virtual Screening

Towards the Atomic-Level Analysis of Ground-State Electronic Structures of Solid Materials via Prediction from Core-Loss Spectra

High-Speed Cyclic Voltammetry Regressions Using Machine Learning

Learning RMSD to Improve Protein-Ligand Scoring and Pose Selection

A deep learning approach for quantum dots sizing from wide-angle X-ray scattering data

7 results in Keywords: Convolutional Neural Networks