https://puma.ub.uni-stuttgart.de/tag/kernelPUMA RSS feed for /tag/kernel2026-04-23T06:25:55+02:00https://puma.ub.uni-stuttgart.de/bibtex/20d9e4f97e9687f82660bcd471d24e67a/iew_homepageiew_homepage2025-07-21T13:10:51+02:00Computational_modeling Convolution Convolutional_neural_networks Kernel Kriging Mathematical_models Neurons Synchronous_Reluctance_Machine Topology Training convolutional_neural_network data-driven_surrogate_model drive_cycle_optimization fully_connected_deep_neural_network hp_iew operating_point_dependent_optimization optimization support_vector_regression torque <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Yuancong Gong" itemprop="url" href="/person/19d6e9b793abf92ce931d18c2b3cbde40/author/0"><span itemprop="name">Y. Gong</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Gneiting" itemprop="url" href="/person/19d6e9b793abf92ce931d18c2b3cbde40/author/1"><span itemprop="name">A. Gneiting</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Chongshen Zhao" itemprop="url" href="/person/19d6e9b793abf92ce931d18c2b3cbde40/author/2"><span itemprop="name">C. Zhao</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Nejila Parspour" itemprop="url" href="/person/19d6e9b793abf92ce931d18c2b3cbde40/author/3"><span itemprop="name">N. Parspour</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hao Chen" itemprop="url" href="/person/19d6e9b793abf92ce931d18c2b3cbde40/author/4"><span itemprop="name">H. Chen</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">IEEE Transactions on Industry Applications</span>, </em> </span>(<em><span>2025<meta content="2025" itemprop="datePublished"/></span></em>)</span>https://puma.ub.uni-stuttgart.de/bibtex/2170332c3f0ced359dd0fcfb339ab061b/mathematikmathematik2021-09-29T14:35:10+02:00Kernel anm approximation, control, dynamic feedback from:britsteiner greedy ians optimal principle, programming techniques <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="A. Schmidt" itemprop="url" href="/person/14bfa5b3c1d35696d5b7b3d202217e601/author/0"><span itemprop="name">A. Schmidt</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bernard Haasdonk" itemprop="url" href="/person/14bfa5b3c1d35696d5b7b3d202217e601/author/1"><span itemprop="name">B. Haasdonk</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">IFAC-PapersOnLine</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">51 </span></span>(<span itemprop="issueNumber">2</span>): <span itemprop="pagination">307--312</span></em> </span>(<em><span>2018<meta content="2018" itemprop="datePublished"/></span></em>)<em>9th Vienna International Conference on Mathematical Modelling.</em></span>https://puma.ub.uni-stuttgart.de/bibtex/291f54fe318fd82138164bcd9e2763d27/mathematikmathematik2021-09-29T14:35:10+02:00anm blood dimensionally flow from:britsteiner ians kernel methods, mixed‐dimension models, peripheral real‐time reduced simulations simulations, stenosis, surrogate <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Köppl" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/0"><span itemprop="name">T. Köppl</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gabriele Santin" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/1"><span itemprop="name">G. Santin</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bernard Haasdonk" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/2"><span itemprop="name">B. Haasdonk</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Rainer Helmig" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/3"><span itemprop="name">R. Helmig</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">International Journal for Numerical Methods in Biomedical Engineering</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">34 </span></span>(<span itemprop="issueNumber">8</span>): <span itemprop="pagination">e3095</span></em> </span>(<em><span>2018<meta content="2018" itemprop="datePublished"/></span></em>)<em>e3095 cnm.3095.</em></span>https://puma.ub.uni-stuttgart.de/bibtex/288e9a857661efa99f399e9d4f24b559e/mathematikmathematik2021-09-29T14:35:08+02:00subspace error dynamical kernel a-posteriori from:britsteiner methods, ians nonlinear systems, offline/online decomposition, projection estimates, model anm reduction, <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Daniel Wirtz" itemprop="url" href="/person/1e80ae72fe2c1f9f79f4f7f8f5ce00735/author/0"><span itemprop="name">D. Wirtz</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bernard Haasdonk" itemprop="url" href="/person/1e80ae72fe2c1f9f79f4f7f8f5ce00735/author/1"><span itemprop="name">B. Haasdonk</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Systems &amp; Control Letters</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">61 </span></span>(<span itemprop="issueNumber">1</span>): <span itemprop="pagination">203--211</span></em> </span>(<em><span>2012<meta content="2012" itemprop="datePublished"/></span></em>)</span>https://puma.ub.uni-stuttgart.de/bibtex/2c9ff784e6a0440b80b45055fa2c9df7e/britsteinerbritsteiner2021-09-29T14:33:27+02:00a-posteriori anm decomposition, dynamical error estimates, ians kernel methods, model nonlinear offline/online parameterized projection reduction, subspace systems, <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Daniel Wirtz" itemprop="url" href="/person/1e6dce191069323c30bda8a87cce2913a/author/0"><span itemprop="name">D. Wirtz</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bernard Haasdonk" itemprop="url" href="/person/1e6dce191069323c30bda8a87cce2913a/author/1"><span itemprop="name">B. Haasdonk</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proc. MATHMOD 2012 - 7th Vienna International Conference on Mathematical Modelling</span>, </em></span>(<em><span>2012<meta content="2012" itemprop="datePublished"/></span></em>)</span>https://puma.ub.uni-stuttgart.de/bibtex/291f54fe318fd82138164bcd9e2763d27/britsteinerbritsteiner2021-09-29T14:33:27+02:00anm blood dimensionally flow ians kernel methods, mixed‐dimension models, peripheral real‐time reduced simulations simulations, stenosis, surrogate <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Köppl" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/0"><span itemprop="name">T. Köppl</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gabriele Santin" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/1"><span itemprop="name">G. Santin</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bernard Haasdonk" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/2"><span itemprop="name">B. Haasdonk</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Rainer Helmig" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/3"><span itemprop="name">R. Helmig</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">International Journal for Numerical Methods in Biomedical Engineering</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">34 </span></span>(<span itemprop="issueNumber">8</span>): <span itemprop="pagination">e3095</span></em> </span>(<em><span>2018<meta content="2018" itemprop="datePublished"/></span></em>)<em>e3095 cnm.3095.</em></span>https://puma.ub.uni-stuttgart.de/bibtex/2170332c3f0ced359dd0fcfb339ab061b/britsteinerbritsteiner2021-09-29T14:33:27+02:00Kernel anm approximation, control, dynamic feedback greedy ians optimal principle, programming techniques <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="A. Schmidt" itemprop="url" href="/person/14bfa5b3c1d35696d5b7b3d202217e601/author/0"><span itemprop="name">A. Schmidt</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bernard Haasdonk" itemprop="url" href="/person/14bfa5b3c1d35696d5b7b3d202217e601/author/1"><span itemprop="name">B. Haasdonk</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">IFAC-PapersOnLine</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">51 </span></span>(<span itemprop="issueNumber">2</span>): <span itemprop="pagination">307--312</span></em> </span>(<em><span>2018<meta content="2018" itemprop="datePublished"/></span></em>)<em>9th Vienna International Conference on Mathematical Modelling.</em></span>https://puma.ub.uni-stuttgart.de/bibtex/288e9a857661efa99f399e9d4f24b559e/britsteinerbritsteiner2021-09-29T14:33:27+02:00a-posteriori anm decomposition, dynamical error estimates, ians kernel methods, model nonlinear offline/online projection reduction, subspace systems, <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Daniel Wirtz" itemprop="url" href="/person/1e80ae72fe2c1f9f79f4f7f8f5ce00735/author/0"><span itemprop="name">D. Wirtz</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bernard Haasdonk" itemprop="url" href="/person/1e80ae72fe2c1f9f79f4f7f8f5ce00735/author/1"><span itemprop="name">B. Haasdonk</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Systems &amp; Control Letters</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">61 </span></span>(<span itemprop="issueNumber">1</span>): <span itemprop="pagination">203--211</span></em> </span>(<em><span>2012<meta content="2012" itemprop="datePublished"/></span></em>)</span>https://puma.ub.uni-stuttgart.de/bibtex/2699c9caf6155e0598d9c980105b8118d/mathematikmathematik2018-07-20T10:55:02+02:00a-posteriori decomposition, dynamical error estimates, from:mhartmann ians kernel methods, model nonlinear offline/online projection reduction, subspace systems, vorlaeufig <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="D. Wirtz" itemprop="url" href="/person/1e80ae72fe2c1f9f79f4f7f8f5ce00735/author/0"><span itemprop="name">D. Wirtz</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="B. Haasdonk" itemprop="url" href="/person/1e80ae72fe2c1f9f79f4f7f8f5ce00735/author/1"><span itemprop="name">B. Haasdonk</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Systems and Control Letters</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">61 </span></span>(<span itemprop="issueNumber">1</span>): <span itemprop="pagination">203 - 211</span></em> </span>(<em><span>2012<meta content="2012" itemprop="datePublished"/></span></em>)</span>https://puma.ub.uni-stuttgart.de/bibtex/2832dacbae634d8ae21c67ac44f94850c/mathematikmathematik2018-07-20T10:54:55+02:00blood dimensionally flow from:mhartmann ians kernel methods, mixed-dimension models, peripheral real-time reduced simulations simulations, stenosis, surrogate vorlaeufig <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Köppl" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/0"><span itemprop="name">T. Köppl</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gabriele Santin" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/1"><span itemprop="name">G. Santin</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bernard Haasdonk" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/2"><span itemprop="name">B. Haasdonk</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Rainer Helmig" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/3"><span itemprop="name">R. Helmig</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">International Journal for Numerical Methods in Biomedical Engineering</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">0 </span></span>(<span itemprop="issueNumber">ja</span>): <span itemprop="pagination">e3095</span></em> </span>(<em><span>2018<meta content="2018" itemprop="datePublished"/></span></em>)<em>e3095 cnm.3095.</em></span>https://puma.ub.uni-stuttgart.de/bibtex/2c9ff784e6a0440b80b45055fa2c9df7e/mathematikmathematik2018-07-20T10:54:37+02:00a-posteriori decomposition, dynamical error estimates, from:mhartmann ians kernel methods, model nonlinear offline/online parameterized projection reduction, subspace systems, vorlaeufig <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Daniel Wirtz" itemprop="url" href="/person/1e6dce191069323c30bda8a87cce2913a/author/0"><span itemprop="name">D. Wirtz</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bernard Haasdonk" itemprop="url" href="/person/1e6dce191069323c30bda8a87cce2913a/author/1"><span itemprop="name">B. Haasdonk</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proc. MATHMOD 2012 - 7th Vienna International Conference on Mathematical Modelling</span>, </em></span>(<em><span>2012<meta content="2012" itemprop="datePublished"/></span></em>)</span>https://puma.ub.uni-stuttgart.de/bibtex/2699c9caf6155e0598d9c980105b8118d/mhartmannmhartmann2018-07-20T10:54:15+02:00a-posteriori decomposition, dynamical error estimates, kernel methods, model nonlinear offline/online projection reduction, subspace systems, vorlaeufig <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="D. Wirtz" itemprop="url" href="/person/1e80ae72fe2c1f9f79f4f7f8f5ce00735/author/0"><span itemprop="name">D. Wirtz</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="B. Haasdonk" itemprop="url" href="/person/1e80ae72fe2c1f9f79f4f7f8f5ce00735/author/1"><span itemprop="name">B. Haasdonk</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Systems and Control Letters</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">61 </span></span>(<span itemprop="issueNumber">1</span>): <span itemprop="pagination">203 - 211</span></em> </span>(<em><span>2012<meta content="2012" itemprop="datePublished"/></span></em>)</span>https://puma.ub.uni-stuttgart.de/bibtex/2832dacbae634d8ae21c67ac44f94850c/mhartmannmhartmann2018-07-20T10:54:15+02:00blood dimensionally flow kernel methods, mixed-dimension models, peripheral real-time reduced simulations simulations, stenosis, surrogate vorlaeufig <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Köppl" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/0"><span itemprop="name">T. Köppl</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gabriele Santin" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/1"><span itemprop="name">G. Santin</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bernard Haasdonk" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/2"><span itemprop="name">B. Haasdonk</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Rainer Helmig" itemprop="url" href="/person/1979f2097ba9c22d67096e59e5c6d7a3e/author/3"><span itemprop="name">R. Helmig</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">International Journal for Numerical Methods in Biomedical Engineering</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">0 </span></span>(<span itemprop="issueNumber">ja</span>): <span itemprop="pagination">e3095</span></em> </span>(<em><span>2018<meta content="2018" itemprop="datePublished"/></span></em>)<em>e3095 cnm.3095.</em></span>https://puma.ub.uni-stuttgart.de/bibtex/2c9ff784e6a0440b80b45055fa2c9df7e/mhartmannmhartmann2018-07-20T10:54:15+02:00a-posteriori decomposition, dynamical error estimates, kernel methods, model nonlinear offline/online parameterized projection reduction, subspace systems, vorlaeufig <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Daniel Wirtz" itemprop="url" href="/person/1e6dce191069323c30bda8a87cce2913a/author/0"><span itemprop="name">D. Wirtz</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bernard Haasdonk" itemprop="url" href="/person/1e6dce191069323c30bda8a87cce2913a/author/1"><span itemprop="name">B. Haasdonk</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proc. MATHMOD 2012 - 7th Vienna International Conference on Mathematical Modelling</span>, </em></span>(<em><span>2012<meta content="2012" itemprop="datePublished"/></span></em>)</span>