Mikel Landajuela

17 papers A* 6Journal 10Unranked 1
YearRankTypeTitle / Venue / Authors
2026 A* conf
Machine Learning Models Assisting the Development of Antibody Therapeutics and Vaccines - an Emerging Trend.
AAAI
Felipe Leno da Silva, Mikel Landajuela, Edwin A. Saada, Piyush Karande, Sudeep Sarma, Igor D'Angelo, Simone Conti, Daniel M. Faissol
2025 J jnl
Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics.
CoRR
Conor F. Hayes, Felipe Leno da Silva, Jiachen Yang, T. Nathan Mundhenk, Chak Shing Lee, Jacob F. Pettit, Claudio Santiago, Sookyung Kim, Joanne Taery Kim, Ignacio Aravena Solis, Ruben Glatt, Andre R. Goncalves, Alexander Ladd, Ahmet Can Solak, Thomas Desautels, Daniel M. Faissol, Brenden K. Petersen, Mikel Landajuela
2025 A* conf
DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces.
AAAI
Jacob F. Pettit, Chak Shing Lee, Jiachen Yang, Alex Ho, Daniel M. Faissol, Brenden K. Petersen, Mikel Landajuela
2025 J jnl
Language model-accelerated deep symbolic optimization.
Neural Comput. Appl.
Felipe Leno da Silva, Andre R. Goncalves, Sam Nguyen, Denis Vashchenko, Ruben Glatt, Thomas Desautels, Mikel Landajuela, Daniel M. Faissol, Brenden K. Petersen
2025 J jnl
SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation.
IEEE Trans. Evol. Comput.
Fabrício Olivetti de França, Marco Virgolin, Michael Kommenda, Maimuna S. Majumder, Miles D. Cranmer, Guilherme Espada, Leon Ingelse, Alcides Fonseca, Mikel Landajuela, Brenden K. Petersen, Ruben Glatt, T. Nathan Mundhenk, Chak Shing Lee, Jacob D. Hochhalter, David L. Randall, P. Kamienny, Hengzhe Zhang, Grant Dick, Alessandro Simon, Bogdan Burlacu, Jaan Kasak, Meera Vieira Machado, Casper Wilstrup, William G. La Cava
2024 J jnl
DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces.
CoRR
Jacob F. Pettit, Chak Shing Lee, Jiachen Yang, Alex Ho, Daniel M. Faissol, Brenden K. Petersen, Mikel Landajuela
2023 J jnl
Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition.
CoRR
Fabrício Olivetti de França, Marco Virgolin, Michael Kommenda, Maimuna S. Majumder, Miles D. Cranmer, Guilherme Espada, Leon Ingelse, Alcides Fonseca, Mikel Landajuela, Brenden K. Petersen, Ruben Glatt, T. Nathan Mundhenk, Chak Shing Lee, Jacob D. Hochhalter, David L. Randall, P. Kamienny, H. Zhang, Grant Dick, Alessandro Simon, Bogdan Burlacu, Jaan Kasak, Meera Vieira Machado, Casper Wilstrup, William G. La Cava
2022 A* conf
A Unified Framework for Deep Symbolic Regression.
NeurIPS
Mikel Landajuela, Chak Shing Lee, Jiachen Yang, Ruben Glatt, Cláudio P. Santiago, Ignacio Aravena, Terrell Nathan Mundhenk, Garrett Mulcahy, Brenden K. Petersen
2022 — conf
Intracardiac Electrical Imaging Using the 12-Lead ECG: A Machine Learning Approach Using Synthetic Data.
CinC
Mikel Landajuela, Rushil Anirudh, Joe Loscazo, Robert Blake
2021 A* conf
Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients.
ICLR
Brenden K. Petersen, Mikel Landajuela, T. Nathan Mundhenk, Cláudio Prata Santiago, Sookyung Kim, Joanne Taery Kim
2021 A* conf
Discovering symbolic policies with deep reinforcement learning.
ICML
Mikel Landajuela, Brenden K. Petersen, Sookyung Kim, Cláudio P. Santiago, Ruben Glatt, T. Nathan Mundhenk, Jacob F. Pettit, Daniel M. Faissol
2021 J jnl
Distilling Wikipedia mathematical knowledge into neural network models.
CoRR
Joanne Taery Kim, Mikel Landajuela, Brenden K. Petersen
2021 J jnl
Improving exploration in policy gradient search: Application to symbolic optimization.
CoRR
Mikel Landajuela, Brenden K. Petersen, Soo K. Kim, Cláudio P. Santiago, Ruben Glatt, T. Nathan Mundhenk, Jacob F. Pettit, Daniel M. Faissol
2021 J jnl
Incorporating domain knowledge into neural-guided search.
CoRR
Brenden K. Petersen, Cláudio P. Santiago, Mikel Landajuela
2021 A* conf
Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding.
NeurIPS
T. Nathan Mundhenk, Mikel Landajuela, Ruben Glatt, Cláudio P. Santiago, Daniel M. Faissol, Brenden K. Petersen
2021 J jnl
Symbolic Regression via Neural-Guided Genetic Programming Population Seeding.
CoRR
T. Nathan Mundhenk, Mikel Landajuela, Ruben Glatt, Cláudio P. Santiago, Daniel M. Faissol, Brenden K. Petersen
2015 J jnl
Fully decoupled time-marching schemes for incompressible fluid/thin-walled structure interaction.
J. Comput. Phys.
Miguel A. Fernández, Mikel Landajuela, Marina Vidrascu