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Viktor Drgan

Showing results (1-10 of 12) with videos related to

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Molecules (Basel, Switzerland)|January 26, 2020
Hepatotoxicity Modeling Using Counter-Propagation Artificial Neural Networks: Handling an Imbalanced Classification ProblemBenjamin Bajželj, Viktor Drgan
International Journal of Molecular Sciences|April 30, 2021
Application of Supervised SOM Algorithms in Predicting the Hepatotoxic Potential of DrugsViktor Drgan, Benjamin Bajželj
Journal of Chromatography. A|August 15, 2009
Computational method for modeling of gradient separation in ion-exchange chromatographyViktor Drgan, Marjana Novic, Milko Novic
Analytica Chimica Acta|October 4, 2011
Optimization of gradient profiles in ion-exchange chromatography using computer simulation programsViktor Drgan, Darja Kotnik, Marjana Novič
Food Chemistry|February 5, 2014
Multi-element analysis of wines by ICP-MS and ICP-OES and their classification according to geographical origin in SloveniaVid S Selih, Martin Sala, Viktor Drgan
International Journal of Molecular Sciences|April 27, 2024
Merging Counter-Propagation and Back-Propagation Algorithms: Overcoming the Limitations of Counter-Propagation Neural Network ModelsViktor Drgan, Katja Venko, Janja Sluga, et al.
Analytica Chimica Acta|December 25, 2012
Assessment of applicability domain for multivariate counter-propagation artificial neural network predictive models by minimum euclidean distance space analysis: a case studyNikola Minovski, Špela Župerl, Viktor Drgan, et al.
Journal of Chromatography. A|February 22, 2008
Hard modeling of ion chromatography separations on hydroxide-selective stationary phaseViktor Drgan, Marjana Novic, Boris Pihlar, et al.
Chemistry Central Journal|November 1, 2013
Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptorsSisir Nandi, Alessandro Monesi, Viktor Drgan, et al.
Journal of Cheminformatics|November 1, 2017
CPANNatNIC software for counter-propagation neural network to assist in read-acrossViktor Drgan, Špela Župerl, Marjan Vračko, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Molecules (Basel, Switzerland)|January 26, 2020
Hepatotoxicity Modeling Using Counter-Propagation Artificial Neural Networks: Handling an Imbalanced Classification ProblemBenjamin Bajželj, Viktor Drgan
International Journal of Molecular Sciences|April 30, 2021
Application of Supervised SOM Algorithms in Predicting the Hepatotoxic Potential of DrugsViktor Drgan, Benjamin Bajželj
Journal of Chromatography. A|August 15, 2009
Computational method for modeling of gradient separation in ion-exchange chromatographyViktor Drgan, Marjana Novic, Milko Novic
Analytica Chimica Acta|October 4, 2011
Optimization of gradient profiles in ion-exchange chromatography using computer simulation programsViktor Drgan, Darja Kotnik, Marjana Novič
Food Chemistry|February 5, 2014
Multi-element analysis of wines by ICP-MS and ICP-OES and their classification according to geographical origin in SloveniaVid S Selih, Martin Sala, Viktor Drgan
International Journal of Molecular Sciences|April 27, 2024
Merging Counter-Propagation and Back-Propagation Algorithms: Overcoming the Limitations of Counter-Propagation Neural Network ModelsViktor Drgan, Katja Venko, Janja Sluga, et al.
Analytica Chimica Acta|December 25, 2012
Assessment of applicability domain for multivariate counter-propagation artificial neural network predictive models by minimum euclidean distance space analysis: a case studyNikola Minovski, Špela Župerl, Viktor Drgan, et al.
Journal of Chromatography. A|February 22, 2008
Hard modeling of ion chromatography separations on hydroxide-selective stationary phaseViktor Drgan, Marjana Novic, Boris Pihlar, et al.
Chemistry Central Journal|November 1, 2013
Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptorsSisir Nandi, Alessandro Monesi, Viktor Drgan, et al.
Journal of Cheminformatics|November 1, 2017
CPANNatNIC software for counter-propagation neural network to assist in read-acrossViktor Drgan, Špela Župerl, Marjan Vračko, et al.
Pageof 2