Genetic Programming Bibliography entries for Karl Michael Garbrecht

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GP coauthors/coeditors: Geoffrey F Bomarito, Patrick E Leser, Nolan Craig McGee Strauss, Jacob Dean Hochhalter, Donovan Keith Birky, Brian Lester, John M Emery,

Genetic Programming Articles by Karl Michael Garbrecht

• Karl Garbrecht and Donovan Birky and Brian Lester and John Emery and Jacob Hochhalter. Complementing a continuum thermodynamic approach to constitutive modeling with symbolic regression. Journal of the Mechanics and Physics of Solids, 181:105472, 2023. details

• G. F. Bomarito and P. E. Leser and N. C. M. Strauss and K. M. Garbrecht and J. D. Hochhalter. Automated learning of interpretable models with quantified uncertainty. Computer Methods in Applied Mechanics and Engineering, 403:115732, 2023. details

Genetic Programming PhD doctoral thesis Karl Michael Garbrecht

• Karl Michael Garbrecht. A physics-informed machine learning framework for constitutive model development. PhD thesis, Department of Mechanical Engineering, The University of Utah, USA, 2024. details

Genetic Programming conference papers by Karl Michael Garbrecht

• Geoffrey Bomarito and Patrick Leser and Nolan Strauss and Karl Garbrecht and Jacob Hochhalter. Bayesian Model Selection for Reducing Bloat and Overfitting in Genetic Programming for Symbolic Regression. In Heike Trautmann and Carola Doerr and Alberto Moraglio and Thomas Bartz-Beielstein and Bogdan Filipic and Marcus Gallagher and Yew-Soon Ong and Abhishek Gupta and Anna V Kononova and Hao Wang and Michael Emmerich and Peter A. N. Bosman and Daniela Zaharie and Fabio Caraffini and Johann Dreo and Anne Auger and Konstantin Dietric and Paul Dufosse and Tobias Glasmachers and Nikolaus Hansen and Olaf Mersmann and Petr Posik and Tea Tusar and Dimo Brockhoff and Tome Eftimov and Pascal Kerschke and Boris Naujoks and Mike Preuss and Vanessa Volz and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Mark Coletti and Catherine (Katie) Schuman and Eric ``Siggy'' Scott and Robert Patton and Paul Wiegand and Jeffrey K. Bassett and Chathika Gunaratne and Tinkle Chugh and Richard Allmendinger and Jussi Hakanen and Daniel Tauritz and John Woodward and Manuel Lopez-Ibanez and John McCall and Jaume Bacardit and Alexander Brownlee and Stefano Cagnoni and Giovanni Iacca and David Walker and Jamal Toutouh and UnaMay O'Reilly and Penousal Machado and Joao Correia and Sergio Nesmachnow and Josu Ceberio and Rafael Villanueva and Ignacio Hidalgo and Francisco Fernandez de Vega and Giuseppe Paolo and Alex Coninx and Antoine Cully and Adam Gaier and Stefan Wagner and Michael Affenzeller and Bobby R. Bruce and Vesna Nowack and Aymeric Blot and Emily Winter and William B. Langdon and Justyna Petke and Silvino Fernandez Alzueta and Pablo Valledor Pellicer and Thomas Stuetzle and David Paetzel and Alexander Wagner and Michael Heider and Nadarajen Veerapen and Katherine Malan and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Mohammad Nabi Omidvar and Yuan Sun and Ernesto Tarantino and De Falco Ivanoe and Antonio Della Cioppa and Scafuri Umberto and John Rieffel and Jean-Baptiste Mouret and Stephane Doncieux and Stefanos Nikolaidis and Julian Togelius and Matthew C. Fontaine and Serban Georgescu and Francisco Chicano and Darrell Whitley and Oleksandr Kyriienko and Denny Dahl and Ofer Shir and Lee Spector and Alma Rahat and Richard Everson and Jonathan Fieldsend and Handing Wang and Yaochu Jin and Erik Hemberg and Marwa A. Elsayed and Michael Kommenda and William La Cava and Gabriel Kronberger and Steven Gustafson editors, Proceedings of the 2022 Genetic and Evolutionary Computation Conference Companion, pages 526-529, Boston, USA, 2022. Association for Computing Machinery. details