Hünnefeld M, Abbasi R, Ackermann M, Adams J, Aguilar JA, Ahlers M, Ahrens M, Alispach C, Alves AA, Amin NM, An R, Andeen K, Anderson T, Anton G, Argüelles C, Ashida Y, Axani S, Bai X, Balagopal AV, Barbano A, Barwick SW, Bastian B, Basu V, Baur S, Bay R, Beatty JJ, Becker KH, Becker Tjus J, Bellenghi C, BenZvi S, Berley D, Bernardini E, Besson DZ, Binder G, Bindig D, Blaufuss E, Blot S, Boddenberg M, Bontempo F, Borowka J, Böser S, Botner O, Böttcher J, Bourbeau E, Bradascio F, Braun J, Bron S, Brostean-Kaiser J, Browne S, Burgman A, Burley RT, Busse RS, Campana MA, Carnie-Bronca EG, Chen C, Chirkin D, Choi K, Clark BA, Clark K, Classen L, Coleman A, Collin GH, Conrad JM, Coppin P, Correa P, Cowen DF, Cross R, Dappen C, Dave P, De Clercq C, DeLaunay JJ, Dembinski H, Deoskar K, De Ridder S, Desai A, Desiati P, de Vries KD, de Wasseige G, de With M, DeYoung T, Dharani S, Diaz A, Díaz-Vélez JC, Dittmer M, Dujmovic H, Dunkman M, DuVernois MA, Dvorak E, Ehrhardt T, Eller P, Engel R, Erpenbeck H, Evans J, Evenson PA, Fan KL, Fazely AR, Fiedlschuster S, Fienberg AT, Filimonov K, Finley C, Fischer L, Fox D, Franckowiak A, Friedman E, Fritz A, Fürst P, Gaisser TK, Gallagher J, Ganster E, Garcia A, Garrappa S, Gerhardt L, Ghadimi A, Glaser C, Glauch T, Glüsenkamp T, Goldschmidt A, Gonzalez JG, Goswami S, Grant D, Grégoire T, Griswold S, Gündüz M, Günther C, Haack C, Hallgren A, Halliday R, Halve L, Halzen F, Ha Minh M, Hanson K, Hardin J, Harnisch AA, Haungs A, Hauser S, Hebecker D, Helbing K, Henningsen F, Hettinger EC, Hickford S, Hignight J, Hill C, Hill GC, Hoffman KD, Hoffmann R, Hoinka T, Hokanson-Fasig B, Hoshina K, Huang F, Huber M, Huber T, Hultqvist K, Hussain R, In S, Iovine N, Ishihara A, Jansson M, Japaridze GS, Jeong M, Jones BJ, Kang D, Kang W, Kang X, Kappes A, Kappesser D, Karg T, Karl M, Karle A, Katz U, Kauer M, Kellermann M, Kelley JL, Kheirandish A, Kin K, Kintscher T, Kiryluk J, Klein SR, Koirala R, Kolanoski H, Kontrimas T, Köpke L, Kopper C, Kopper S, Koskinen DJ, Koundal P, Kovacevich M, Kowalski M, Kozynets T, Kun E, Kurahashi N, Lad N, Lagunas Gualda C, Lanfranchi JL, Larson MJ, Lauber F, Lazar JP, Lee JW, Leonard K, Leszczyńska A, Li Y, Lincetto M, Liu QR, Liubarska M, Lohfink E, Lozano Mariscal CJ, Lu L, Lucarelli F, Ludwig A, Luszczak W, Lyu Y, Ma WY, Madsen J, Mahn KB, Makino Y, Mancina S, Mariş IC, Maruyama R, Mase K, McElroy T, McNally F, Mead JV, Meagher K, Medina A, Meier M, Meighen-Berger S, Micallef J, Mockler D, Montaruli T, Moore RW, Morse R, Moulai M, Naab R, Nagai R, Naumann U, Necker J, Nguyên LV, Niederhausen H, Nisa MU, Nowicki SC, Nygren DR, Obertacke Pollmann A, Oehler M, Olivas A, O’Sullivan E, Pandya H, Pankova DV, Park N, Parker GK, Paudel EN, Paul L, Pérez de los Heros C, Peters L, Peterson J, Philippen S, Pieloth D, Pieper S, Pittermann M, Pizzuto A, Plum M, Popovych Y, Porcelli A, Prado Rodriguez M, Price PB, Pries B, Przybylski GT, Raab C, Raissi A, Rameez M, Rawlins K, Rea IC, Rehman A, Reichherzer P, Reimann R, Renzi G, Resconi E, Reusch S, Rhode W, Richman M, Riedel B, Roberts EJ, Robertson S, Roellinghoff G, Rongen M, Rott C, Ruhe T, Ryckbosch D, Rysewyk Cantu D, Safa I, Saffer J, Sanchez Herrera SE, Sandrock A, Sandroos J, Santander M, Sarkar S, Satalecka K, Scharf M, Schaufel M, Schieler H, Schindler S, Schlunder P, Schmidt T, Schneider A, Schneider J, Schröder FG, Schumacher L, Schwefer G, Sclafani S, Seckel D, Seunarine S, Sharma A, Shefali S, Silva M, Skrzypek B, Smithers B, Snihur R, Soedingrekso J, Soldin D, Spannfellner C, Spiczak GM, Spiering C, Stachurska J, Stamatikos M, Stanev T, Stein R, Stettner J, Steuer A, Stezelberger T, Stürwald T, Stuttard T, Sullivan GW, Taboada I, Tenholt F, Ter-Antonyan S, Tilav S, Tischbein F, Tollefson K, Tomankova L, Tönnis C, Toscano S, Tosi D, Trettin A, Tselengidou M, Tung CF, Turcati A, Turcotte R, Turley CF, Twagirayezu JP, Ty B, Unland Elorrieta MA, Valtonen-Mattila N, Vandenbroucke J, van Eijndhoven N, Vannerom D, van Santen J, Verpoest S, Vraeghe M, Walck C, Watson TB, Weaver C, Weigel P, Weindl A, Weiss MJ, Weldert J, Wendt C, Werthebach J, Weyrauch M, Whitehorn N, Wiebusch CH, Williams DR, Wolf M, Woschnagg K, Wrede G, Wulff J, Xu XW, Xu Y, Yanez JP, Yoshida S, Yu S, Yuan T, Zhang Z (2022)
Publication Type: Conference contribution
Publication year: 2022
Publisher: Sissa Medialab Srl
Book Volume: 395
Conference Proceedings Title: Proceedings of Science
Event location: Virtual, Berlin, DEU
The field of deep learning has become increasingly important for particle physics experiments, yielding a multitude of advances, predominantly in event classification and reconstruction tasks. Many of these applications have been adopted from other domains. However, data in the field of physics are unique in the context of machine learning, insofar as their generation process and the laws and symmetries they abide by are usually well understood. Most commonly used deep learning architectures fail at utilizing this available information. In contrast, more traditional likelihood-based methods are capable of exploiting domain knowledge, but they are often limited by computational complexity. In this contribution, a hybrid approach is presented that utilizes generative neural networks to approximate the likelihood, which may then be used in a traditional maximum-likelihood setting. Domain knowledge, such as invariances and detector characteristics, can easily be incorporated in this approach. The hybrid approach is illustrated by the example of event reconstruction in IceCube.
APA:
Hünnefeld, M., Abbasi, R., Ackermann, M., Adams, J., Aguilar, J.A., Ahlers, M.,... Zhang, Z. (2022). Combining Maximum-Likelihood with Deep Learning for Event Reconstruction in IceCube. In Proceedings of Science. Virtual, Berlin, DEU: Sissa Medialab Srl.
MLA:
Hünnefeld, Mirco, et al. "Combining Maximum-Likelihood with Deep Learning for Event Reconstruction in IceCube." Proceedings of the 37th International Cosmic Ray Conference, ICRC 2021, Virtual, Berlin, DEU Sissa Medialab Srl, 2022.
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