Jacob D. Hochhalter

Publication Activity (10 Years)

Years Active: 2022-2024
Publications (10 Years): 5

Top Topics

Differential Equations

Symbolic Regression

Top Venues

GECCO Companion

Publications

Zachary Bastiani, Robert M. Kirby, Jacob D. Hochhalter, Shandian Zhe
Complexity-Aware Deep Symbolic Regression with Robust Risk-Seeking Policy Gradients. CoRR (2024)
Fabrício Olivetti de França, Marco Virgolin, Michael Kommenda, M. S. Majumder, Miles D. Cranmer, Guilherme Espada, Leon Ingelse, Alcides Fonseca, Mikel Landajuela, B. Petersen, Ruben Glatt, T. Nathan Mundhenk, C. S. Lee, Jacob D. Hochhalter, David L. Randall, P. Kamienny, H. Zhang, G. Dick, A. Simon, Bogdan Burlacu, Jaan Kasak, Meera Vieira Machado, Casper Wilstrup, William G. La Cava
Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition. CoRR (2023)
Hongsup Oh, Roman Amici, Geoffrey F. Bomarito, Shandian Zhe, Robert Kirby, Jacob D. Hochhalter
Genetic Programming Based Symbolic Regression for Analytical Solutions to Differential Equations. CoRR (2023)
David L. Randall, Tyler S. Townsend, Jacob D. Hochhalter, Geoffrey F. Bomarito
Bingo: a customizable framework for symbolic regression with genetic programming. GECCO Companion (2022)
Geoffrey F. Bomarito, Patrick E. Leser, N. C. M. Strauss, K. M. Garbrecht, Jacob D. Hochhalter
Automated Learning of Interpretable Models with Quantified Uncertainty. CoRR (2022)