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56w,/citations/images/avatar_scholar_128.png 128w" width="56" height="56"></span></a><div><a href="/citations?user=zEQGLhoAAAAJ&amp;hl=en">Lev Dudko</a></div></div></div></div><div id="gs_bdy_ccl" role="main"><div id="gsc_vcpb" data-edit-link="/citations?view_op=edit_citation&amp;hl=en&amp;user=zEQGLhoAAAAJ&amp;sortby=title&amp;citation_for_view=zEQGLhoAAAAJ:7h3R5G_fGvwC&amp;citation_for_view=zEQGLhoAAAAJ:7h3R5G_fGvwC&amp;back_view_op=view_citation"><form method="post" id="gsc_vcpb_btns" action="/citations?view_op=view_citation&amp;hl=en"><input type="hidden" name="xsrf" value="ADIE8skAAAAAZ0isku4duOSRSZ74H4mrTMXU2T0"><input type="hidden" name="s" value="zEQGLhoAAAAJ:7h3R5G_fGvwC"><input type="hidden" name="continue" value="/citations?view_op=list_works&amp;hl=en&amp;hl=en&amp;user=zEQGLhoAAAAJ&amp;sortby=title"></form><div id="gsc_oci_title_wrapper"><div id="gsc_oci_title_gg"><div class="gsc_oci_title_ggi"><a href="https://link.springer.com/article/10.1007/s41781-020-00041-z" data-clk="hl=en&amp;sa=T&amp;ei=EltHZ5-8L6aIy9YPj4bQgAQ"><span class='gsc_vcd_title_ggt'>[HTML]</span> from springer.com</a></div><div class="gsc_oci_title_ggi"><a href="https://link.springer.com/content/pdf/10.1007/s41781-020-00041-z.pdf" data-clk="hl=en&amp;sa=T&amp;ei=EltHZ5-8L6aIy9YPj4bQgAQ">Full View</a></div></div><div id="gsc_oci_title"><a class="gsc_oci_title_link" href="https://link.springer.com/article/10.1007/s41781-020-00041-z" data-clk="hl=en&amp;sa=T&amp;ei=EltHZ5-8L6aIy9YPj4bQgAQ">A deep neural network for simultaneous estimation of b jet energy and resolution</a></div></div><div id="gsc_oci_table"><div class="gs_scl"><div class="gsc_oci_field">Authors</div><div class="gsc_oci_value">Albert M Sirunyan, Armen Tumasyan, Wolfgang Adam, Federico Ambrogi, Thomas Bergauer, Marko Dragicevic, Janos Erö, A Escalante Del Valle, Martin Flechl, Rudolf Fruehwirth, Manfred Jeitler, Natascha Krammer, Ilse Krätschmer, Dietrich Liko, Thomas Madlener, Ivan Mikulec, Navid Rad, Jochen Schieck, Robert Schöfbeck, Markus Spanring, Daniel Spitzbart, Wolfgang Waltenberger, C-E Wulz, Mateusz Zarucki, Vladimir Drugakov, Vladimir Mossolov, J Suarez Gonzalez, Mohamed Rashad Darwish, Eddi A De Wolf, D Di Croce, Xavier Janssen, Aleksandra Lelek, Maxim Pieters, H Rejeb Sfar, H Van Haevermaet, P Van Mechelen, S Van Putte, N Van Remortel, Freya Blekman, Emil Sørensen Bols, Simranjit Singh Chhibra, Jorgen D’Hondt, Jarne De Clercq, Denys Lontkovskyi, Steven Lowette, Ivan Marchesini, Seth Moortgat, Quentin Python, Kirill Skovpen, Stefaan Tavernier, W Van Doninck, P Van Mulders, Diego Beghin, Bugra Bilin, Barbara Clerbaux, Gilles De Lentdecker, Hugo Delannoy, Brian Dorney, Laurent Favart, Anastasia Grebenyuk, Amandeep Kaur Kalsi, Andrey Popov, Nicolas Postiau, Elizabeth Starling, Laurent Thomas, C Vander Velde, P Vanlaer, D Vannerom, T Cornelis, D Dobur, I Khvastunov, M Niedziela, C Roskas, M Tytgat, W Verbeke, B Vermassen, M Vit, O Bondu, G Bruno, C Caputo, P David, C Delaere, M Delcourt, A Giammanco, V Lemaitre, J Prisciandaro, A Saggio, M Vidal Marono, P Vischia, J Zobec, FL Alves, GA Alves, G Correia Silva, C Hensel, A Moraes, P Rebello Teles, E Belchior Batista Das Chagas, W Carvalho, J Chinellato, E Coelho, EM Da Costa, GG Da Silveira, D De Jesus Damiao, C De Oliveira Martins, S Fonseca De Souza, LM Huertas Guativa, H Malbouisson, J Martins, D Matos Figueiredo, M Medina Jaime, M Melo De Almeida, C Mora Herrera, L Mundim, H Nogima, WL Prado Da Silva, LJ Sanchez Rosas, A Santoro, A Sznajder, M Thiel, EJ Tonelli Manganote, F Torres Da Silva De Araujo, A Vilela Pereira, CA Bernardes, L Calligaris, TR Fernandez Perez Tomei, EM Gregores, DS Lemos, PG Mercadante, SF Novaes, SandraS Padula, A Aleksandrov, G Antchev, R Hadjiiska, P Iaydjiev, M Misheva, M Rodozov, M Shopova, G Sultanov, M Bonchev, A Dimitrov, T Ivanov, L Litov, B Pavlov, P Petkov, W Fang, X Gao, L Yuan, M Ahmad, Z Hu, Y Wang</div></div><div class="gs_scl"><div class="gsc_oci_field">Publication date</div><div class="gsc_oci_value">2020/12</div></div><div class="gs_scl"><div class="gsc_oci_field">Journal</div><div class="gsc_oci_value">Computing and software for big science</div></div><div class="gs_scl"><div class="gsc_oci_field">Volume</div><div class="gsc_oci_value">4</div></div><div class="gs_scl"><div class="gsc_oci_field">Pages</div><div class="gsc_oci_value">1-20</div></div><div class="gs_scl"><div class="gsc_oci_field">Publisher</div><div class="gsc_oci_value">Springer International Publishing</div></div><div class="gs_scl"><div class="gsc_oci_field">Description</div><div class="gsc_oci_value" id="gsc_oci_descr"><div class="gsh_small"> <div class="gsh_csp">We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton–proton collisions at an energy of <svg class="gs_fsvg" aria-label=" s = 13 TeV " width="79px" height="15px" style="vertical-align:-3px;"><g transform="matrix(0.01400, 0.00000, 0.00000, 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The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 <svg class="gs_fsvg" aria-label=" fb - 1 " width="30px" height="13px" style="vertical-align:0px;"><g transform="matrix(0.01400, 0.00000, 0.00000, 0.01400, 0.00000, 12.91613)"><g><g><g transform="translate(166.66699, 0.00000)"><g><g><path transform="scale(0.48828, -0.48828)" d="M 66 0 V 72 Q 135 72 180 83 T 225 137 V 811 H 68 V 883 H 225 V 1128 Q 225 1194 252 1251 T 326 1352 T 433 1419 T 559 1444 Q 628 1444 683 1403 T 739 1294 Q 739 1255 712 1228 T 647 1202 Q 608 1202 580 1228 T 553 1294 Q 553 1358 608 1380 Q 575 1391 549 1391 Q 489 1391 446 1348 T 383 1245 T 362 1124 V 883 H 598 V 811 H 369 V 137 Q 369 95 429 83 T 567 72 V 0 H 66 Z "/><path transform="matrix(0.48828, 0.00000, 0.00000, -0.48828, 383.33899, 0.00000)" d="M 213 0 V 1212 Q 213 1267 196 1291 T 149 1321 T 53 1327 V 1399 L 356 1421 V 780 Q 390 818 435 846 T 533 890 T 639 905 Q 731 905 809 868 T 946 766 T 1036 616 T 1069 442 Q 1069 318 1008 211 T 843 40 T 614 -23 Q 536 -23 463 17 T 342 123 L 272 0 H 213 Z M 362 201 Q 396 126 460 78 T 602 31 Q 708 31 773 92 T 865 246 T 891 442 Q 891 615 846 705 Q 826 745 791 779 T 714 832 T 625 852 Q 543 852 473 808 T 362 692 V 201 Z "/></g><g transform="translate(938.89899, -457.78030)"><path transform="scale(0.34180, -0.34180)" d="M 268 461 Q 248 464 234 477 T 221 512 Q 221 554 268 561 H 1559 Q 1606 554 1606 512 Q 1606 491 1592 477 T 1559 461 H 268 Z "/><path transform="matrix(0.34180, 0.00000, 0.00000, -0.34180, 624.98102, 0.00000)" d="M 233 0 V 82 Q 516 82 516 143 V 1202 Q 401 1147 219 1147 V 1229 Q 341 1229 447 1258 T 629 1360 H 666 Q 685 1355 690 1335 V 143 Q 690 82 973 82 V 0 H 233 Z "/></g></g></g></g></g></g></svg>. A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to <svg class="gs_fsvg" aria-label=" b b ¯ " width="16px" height="12px" style="vertical-align:0px;"><g transform="matrix(0.01400, 0.00000, 0.00000, 0.01400, 0.00000, 11.94823)"><g><g><path transform="scale(0.48828, -0.48828)" d="M 213 0 V 1212 Q 213 1267 196 1291 T 149 1321 T 53 1327 V 1399 L 356 1421 V 780 Q 390 818 435 846 T 533 890 T 639 905 Q 731 905 809 868 T 946 766 T 1036 616 T 1069 442 Q 1069 318 1008 211 T 843 40 T 614 -23 Q 536 -23 463 17 T 342 123 L 272 0 H 213 Z M 362 201 Q 396 126 460 78 T 602 31 Q 708 31 773 92 T 865 246 T 891 442 Q 891 615 846 705 Q 826 745 791 779 T 714 832 T 625 852 Q 543 852 473 808 T 362 692 V 201 Z "/><g transform="translate(555.56000, 0.00000)"><g><g><path transform="scale(0.48828, -0.48828)" d="M 213 0 V 1212 Q 213 1267 196 1291 T 149 1321 T 53 1327 V 1399 L 356 1421 V 780 Q 390 818 435 846 T 533 890 T 639 905 Q 731 905 809 868 T 946 766 T 1036 616 T 1069 442 Q 1069 318 1008 211 T 843 40 T 614 -23 Q 536 -23 463 17 T 342 123 L 272 0 H 213 Z M 362 201 Q 396 126 460 78 T 602 31 Q 708 31 773 92 T 865 246 T 891 442 Q 891 615 846 705 Q 826 745 791 779 T 714 832 T 625 852 Q 543 852 473 808 T 362 692 V 201 Z "/></g><g transform="translate(27.78000, -263.44501)"><g><path transform="scale(0.48828, -0.48828)" d="M 141 1137 V 1208 H 881 V 1137 H 141 Z "/></g></g></g></g></g></g></g></svg>.</div></div></div></div><div class="gs_scl"><div class="gsc_oci_field">Total citations</div><div class="gsc_oci_value"><div style="margin-bottom:1em"><a href="https://scholar.google.com/scholar?oi=bibs&amp;hl=en&amp;cites=12587616657764162305,15191254709535081141&amp;as_sdt=5">Cited by 106</a></div><div id="gsc_oci_graph_wrapper"><div id="gsc_oci_graph" style="width:196px;"><div id="gsc_oci_graph_x"></div><div id="gsc_oci_graph_bars"><span class="gsc_oci_g_t" style="left:0px">2019</span><span class="gsc_oci_g_t" style="left:33px">2020</span><span class="gsc_oci_g_t" style="left:66px">2021</span><span class="gsc_oci_g_t" style="left:99px">2022</span><span class="gsc_oci_g_t" style="left:132px">2023</span><span class="gsc_oci_g_t" style="left:165px">2024</span><a href="https://scholar.google.com/scholar?oi=bibs&amp;hl=en&amp;cites=12587616657764162305,15191254709535081141&amp;as_sdt=5&amp;as_ylo=2019&amp;as_yhi=2019" class="gsc_oci_g_a" style="left:5px;height:4px;top:53px;z-index:6"><span class="gsc_oci_g_al">2</span></a><a href="https://scholar.google.com/scholar?oi=bibs&amp;hl=en&amp;cites=12587616657764162305,15191254709535081141&amp;as_sdt=5&amp;as_ylo=2020&amp;as_yhi=2020" class="gsc_oci_g_a" style="left:38px;height:15px;top:42px;z-index:5"><span class="gsc_oci_g_al">7</span></a><a href="https://scholar.google.com/scholar?oi=bibs&amp;hl=en&amp;cites=12587616657764162305,15191254709535081141&amp;as_sdt=5&amp;as_ylo=2021&amp;as_yhi=2021" 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