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Alexander Kensert

Showing results (1-10 of 13) with videos related to

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Journal of Computer-Aided Molecular Design|December 5, 2024
MolGraph: a Python package for the implementation of molecular graphs and graph neural networks with TensorFlow and KerasAlexander Kensert, Gert Desmet, Deirdre Cabooter
Journal of Chromatography. A|December 15, 2023
A perspective on the use of deep deterministic policy gradient reinforcement learning for retention time modeling in reversed-phase liquid chromatographyAlexander Kensert, Gert Desmet, Deirdre Cabooter
Analytica Chimica Acta|November 12, 2024
A hands-on tutorial on quantitative structure-activity relationships using fully expressive graph neural networksAlexander Kensert, Gert Desmet, Deirdre Cabooter
SLAS Discovery : Advancing Life Sciences R & D|January 15, 2019
Transfer Learning with Deep Convolutional Neural Networks for Classifying Cellular Morphological ChangesAlexander Kensert, Philip J Harrison, Ola Spjuth
Journal of Chromatography. A|March 5, 2024
Deep reinforcement learning for the direct optimization of gradient separations in liquid chromatographyAlexander Kensert, Pieter Libin, Gert Desmet, et al.
Journal of Cheminformatics|October 12, 2018
Evaluating parameters for ligand-based modeling with random forest on sparse data setsAlexander Kensert, Jonathan Alvarsson, Ulf Norinder, et al.
Journal of Chromatography. A|December 17, 2023
Automated method development in high-pressure liquid chromatographyEmery Bosten, Alexander Kensert, Gert Desmet, et al.
Journal of Chromatography. A|January 23, 2021
Deep Q-learning for the selection of optimal isocratic scouting runs in liquid chromatographyAlexander Kensert, Gilles Collaerts, Kyriakos Efthymiadis, et al.
Journal of Chromatography. A|April 14, 2021
Deep convolutional autoencoder for the simultaneous removal of baseline noise and baseline drift in chromatogramsAlexander Kensert, Gilles Collaerts, Kyriakos Efthymiadis, et al.
Analytical Chemistry|November 15, 2021
Graph Convolutional Networks for Improved Prediction and Interpretability of Chromatographic Retention DataAlexander Kensert, Robbin Bouwmeester, Kyriakos Efthymiadis, et al.
Pageof 2

Showing results (1-10 of 13) with videos related to

Sort By:
Pageof 2
Journal of Computer-Aided Molecular Design|December 5, 2024
MolGraph: a Python package for the implementation of molecular graphs and graph neural networks with TensorFlow and KerasAlexander Kensert, Gert Desmet, Deirdre Cabooter
Journal of Chromatography. A|December 15, 2023
A perspective on the use of deep deterministic policy gradient reinforcement learning for retention time modeling in reversed-phase liquid chromatographyAlexander Kensert, Gert Desmet, Deirdre Cabooter
Analytica Chimica Acta|November 12, 2024
A hands-on tutorial on quantitative structure-activity relationships using fully expressive graph neural networksAlexander Kensert, Gert Desmet, Deirdre Cabooter
SLAS Discovery : Advancing Life Sciences R & D|January 15, 2019
Transfer Learning with Deep Convolutional Neural Networks for Classifying Cellular Morphological ChangesAlexander Kensert, Philip J Harrison, Ola Spjuth
Journal of Chromatography. A|March 5, 2024
Deep reinforcement learning for the direct optimization of gradient separations in liquid chromatographyAlexander Kensert, Pieter Libin, Gert Desmet, et al.
Journal of Cheminformatics|October 12, 2018
Evaluating parameters for ligand-based modeling with random forest on sparse data setsAlexander Kensert, Jonathan Alvarsson, Ulf Norinder, et al.
Journal of Chromatography. A|December 17, 2023
Automated method development in high-pressure liquid chromatographyEmery Bosten, Alexander Kensert, Gert Desmet, et al.
Journal of Chromatography. A|January 23, 2021
Deep Q-learning for the selection of optimal isocratic scouting runs in liquid chromatographyAlexander Kensert, Gilles Collaerts, Kyriakos Efthymiadis, et al.
Journal of Chromatography. A|April 14, 2021
Deep convolutional autoencoder for the simultaneous removal of baseline noise and baseline drift in chromatogramsAlexander Kensert, Gilles Collaerts, Kyriakos Efthymiadis, et al.
Analytical Chemistry|November 15, 2021
Graph Convolutional Networks for Improved Prediction and Interpretability of Chromatographic Retention DataAlexander Kensert, Robbin Bouwmeester, Kyriakos Efthymiadis, et al.
Pageof 2