Petersen, Brenden K

8 publications

AAAI 2025 DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces Jacob F. Pettit, Chak Shing Lee, Jiachen Yang, Alex Ho, Daniel M. Faissol, Brenden K. Petersen, Mikel Landajuela

ICMLW 2024 Generative Design of Decision Tree Policies for Reinforcement Learning Jacob Pettit, Chak Shing Lee, Jiachen Yang, Alex Ho, Daniel Faissol, Brenden K. Petersen, Mikel Landajuela

NeurIPS 2022 A Unified Framework for Deep Symbolic Regression Mikel Landajuela, Chak Shing Lee, Jiachen Yang, Ruben Glatt, Claudio P Santiago, Ignacio Aravena, Terrell Mundhenk, Garrett Mulcahy, Brenden K Petersen

ICLR 2021 Deep Symbolic Regression: Recovering Mathematical Expressions from Data via Risk-Seeking Policy Gradients Brenden K Petersen, Mikel Landajuela Larma, Terrell N. Mundhenk, Claudio Prata Santiago, Soo Kyung Kim, Joanne Taery Kim

ICML 2021 Discovering Symbolic Policies with Deep Reinforcement Learning Mikel Landajuela, Brenden K Petersen, Sookyung Kim, Claudio P Santiago, Ruben Glatt, Nathan Mundhenk, Jacob F Pettit, Daniel Faissol

ICMLW 2021 Incorporating Domain Knowledge into Neural-Guided Search via in Situ Priors and Constraints Brenden K Petersen, Claudio Santiago, Mikel Landajuela

NeurIPS 2021 Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding Terrell Mundhenk, Mikel Landajuela, Ruben Glatt, Claudio P Santiago, Daniel Faissol, Brenden K Petersen

IJCAI 2020 An Interactive Visualization Platform for Deep Symbolic Regression Joanne Taery Kim, Sookyung Kim, Brenden K. Petersen