@article{UBHD-68954963, author={Bellagente, Marco and Haußmann, Manuel and Luchmann, Michel and Plehn, Tilman}, title={Understanding event-generation networks via uncertainties}, year={2022}, pages={23 S.}, language={eng}, issn={2542-4653}, volume={13}, note={Gesehen am 17.08.2022}, journal={SciPost physics}, doi={10.21468/SciPostPhys.13.1.003}, } @incollection{UBHD-68941122, author={Bellagente, Marco and Haußmann, Manuel and Luchmann, Michel and Plehn, Tilman}, title={Understanding event-generation networks via uncertainties}, year={2021}, pages={26 S.}, language={eng}, note={Gesehen am 13.07.2022}, booktitle={De.arxiv.org}, doi={10.48550/arXiv.2104.04543}, } @article{UBHD-68494079, author={Bollweg, Sven and Haußmann, Manuel and Kasieczka, Gregor and Luchmann, Michel and Plehn, Tilman and Thompson, Jennifer M.}, title={Deep-learning jets with uncertainties and more}, year={2020}, pages={1-25}, language={eng}, issn={2542-4653}, volume={8}, note={Gesehen am 27.02.2020}, journal={SciPost physics}, doi={10.21468/SciPostPhys.8.1.006}, } @article{UBHD-68942697, author={Brivio, Ilaria and Bruggisser, Sebastian and Geoffray, Emma and Killian, Wolfgang and Kr{\"a}mer, Michael and Luchmann, Michel and Plehn, Tilman and Summ, Benjamin}, title={From models to SMEFT and back?}, year={2022}, pages={1-36}, language={eng}, issn={2542-4653}, volume={12}, number={Artikel-ID 036}, note={Gesehen am 15.07.2022}, journal={SciPost physics}, doi={10.21468/SciPostPhys.12.1.036}, } @article{UBHD-69223732, author={Brivio, Ilaria and Bruggisser, Sebastian and Elmer, Nina and Geoffray, Emma and Luchmann, Michel and Plehn, Tilman}, title={To profile or to marginalize - a SMEFT case study}, year={2024}, pages={1-39}, language={eng}, issn={2542-4653}, volume={16}, note={Gesehen am 17.06.2024}, journal={SciPost physics}, doi={10.21468/SciPostPhys.16.1.035}, } @incollection{UBHD-68935680, author={Butter, Anja and Plehn, Tilman and Schumann, Steffen and Badger, Simon and Caron, Sascha and Cranmer, Kyle and Di Bello, Francesco Armando and Dreyer, Etienne and Forte, Stefano and Ganguly, Sanmay and Gonçalves, Dorival and Gross, Eilam and Heimel, Theo and Heinrich, Gudrun and Heinrich, Lukas and Held, Alexander and H{\"o}che, Stefan and Howard, Jessica N. and Ilten, Philip and Isaacson, Joshua and Janßen, Timo and Jones, Stephen and Kado, Marumi and Kagan, Michael and Kasieczka, Gregor and Kling, Felix and Kraml, Sabine and Krause, Claudius and Krauss, Frank and Kr{\"o}ninger, Kevin and Barman, Rahool Kumar and Luchmann, Michel and Magerya, Vitaly and Maitre, Daniel and Malaescu, Bogdan and Maltoni, Fabio and Martini, Till and Mattelaer, Olivier and Nachman, Benjamin and Pitz, Sebastian and Rojo, Juan and Schwartz, Matthew and Shih, David and Siegert, Frank and Stegeman, Roy and Stienen, Bob and Thaler, Jesse and Verheyen, Rob and Whiteson, Daniel and Winterhalder, Ramon and Zupan, Jure}, title={Machine learning and LHC event generation}, year={2022}, pages={1-34}, language={eng}, note={Gesehen am 15.09.2022}, booktitle={Arxiv}, doi={10.48550/arXiv.2203.07460}, } @article{UBHD-69117490, author={Butter, Anja and Plehn, Tilman and Schumann, Steffen and Badger, Simon and Caron, Sascha and Cranmer, Kyle and Di Bello, Francesco Armando and Dreyer, Etienne and Forte, Stefano and Ganguly, Sanmay and Gonçalves, Dorival and Gross, Eilam and Heimel, Theo and Heinrich, Gudrun and Heinrich, Lukas and Held, Alexander and H{\"o}che, Stefan and Howard, Jessica N. and Ilten, Philip and Isaacson, Joshua and Janßen, Timo and Jones, Stephen and Kado, Marumi and Kagan, Michael and Kasieczka, Gregor and Kling, Felix and Kraml, Sabine and Krause, Claudius and Krauss, Frank and Kr{\"o}ninger, Kevin and Barman, Rahool Kumar and Luchmann, Michel and Magerya, Vitaly and Maitre, Daniel and Malaescu, Bogdan and Maltoni, Fabio and Martini, Till and Mattelaer, Olivier and Nachman, Benjamin and Pitz, Sebastian and Rojo, Juan and Schwartz, Matthew and Shih, David and Siegert, Frank and Stegeman, Roy and Stienen, Bob and Thaler, Jesse and Verheyen, Rob and Whiteson, Daniel and Winterhalder, Ramon and Zupan, Jure}, title={Machine learning and LHC event generation}, year={2023}, pages={1-32}, language={eng}, issn={2542-4653}, volume={14}, note={Gesehen am 30.08.2023}, journal={SciPost physics}, doi={10.21468/SciPostPhys.14.4.079}, } @article{UBHD-68882961, author={Kasieczka, Gregor and Luchmann, Michel and Otterpohl, Florian and Plehn, Tilman}, title={Per-object systematics using deep-learned calibration}, year={2020}, pages={20 S.}, language={eng}, issn={2542-4653}, volume={9}, note={Gesehen am 26.02.2022}, journal={SciPost physics}, doi={10.21468/SciPostPhys.9.6.089}, } @book{UBHD-68992806, author={Luchmann, Michel}, title={Making the most of LHC data - Bayesian neural networks and SMEFT global analysis}, address={Heidelberg}, year={2022}, pages={1 Online-Ressource (175 Seiten)}, language={eng}, school={Dissertation, Heidelberg University, 2022}, doi={10.11588/heidok.00032414}, url={https://nbn-resolving.org/urn:nbn:de:bsz:16-heidok-324143}, library={UB}, } @book{UBHD-69028565, author={Luchmann, Michel}, organization={Universit{\"a}t Heidelberg}, title={Making the most of LHC data}, subtitle={Bayesian neural networks and SMEFT global analysis}, address={Heidelberg}, year={2022}, pages={v, 161 Seiten}, language={eng}, school={Dissertation, Heidelberg University, 2022}, library={UB [Signatur: 2023 U 46]}, }