Genetic Programming Bibliography entries for Jacob Dean Hochhalter
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GP coauthors/coeditors:
Geoffrey F Bomarito,
Tyler S Townsend,
K M Stewart,
K V Esham,
John M Emery,
Patrick E Leser,
Nolan Craig McGee Strauss,
Karl Michael Garbrecht,
Fabricio Olivetti de Franca,
Marco Virgolin,
Michael Kommenda,
Maimuna Majumder,
Miles Cranmer,
Guilherme Jorge Nunes Monteiro Espada,
Leon Ingelse,
Alcides Fonseca,
Mikel Landajuela,
Brenden Kyle Petersen,
Ruben Glatt,
T Nathan Mundhenk,
Chak Shing Lee,
David L Randall,
Pierre-Alexandre Kamienny,
Hengzhe Zhang,
Grant Dick,
Alessandro Simon,
Bogdan Burlacu,
Jaan Kasak,
Meera Machado,
Casper Wilstrup,
William La Cava,
Donovan Keith Birky,
Brian Lester,
Cooper K Hansen,
Gary F Whelan,
Hongsup Oh,
Roman Amici,
Shandian Zhe,
Robert Kirby,
Genetic Programming Articles by Jacob Dean Hochhalter
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Cooper K. Hansen and Gary F. Whelan and Jacob D. Hochhalter.
Interpretable machine learning for microstructure-dependent models of fatigue indicator parameters.
International Journal of Fatigue, 178:108019, 2024.
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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.
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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.
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G. F. Bomarito and T. S. Townsend and K. M. Stewart and K. V. Esham and J. M. Emery and J. D. Hochhalter.
Development of interpretable, data-driven plasticity models with symbolic regression.
Computer \& Structures, 252:106557, 2021.
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F. O. de Franca and M. Virgolin and M. Kommenda and M. S. Majumder and M. Cranmer and G. Espada and L. Ingelse and A. Fonseca and M. Landajuela and B. Petersen and R. Glatt and N. Mundhenk and C. S. Lee and J. D. Hochhalter and D. L. Randall and P. Kamienny and H. Zhang and G. Dick and A. Simon and B. Burlacu and Jaan Kasak and Meera Machado and Casper Wilstrup and W. G. La Cava.
SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation.
IEEE Transactions on Evolutionary Computation.
Early Access.
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Genetic Programming conference papers by Jacob Dean Hochhalter
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David L. Randall and Tyler S. Townsend and Jacob D. Hochhalter and Geoffrey F. Bomarito.
Bingo: A Customizable Framework for Symbolic Regression with Genetic Programming. 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 2282-2288, Boston, USA, 2022. Association for Computing Machinery.
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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.
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Genetic Programming other entries for Jacob Dean Hochhalter