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2020 – today
- 2022
[c5]Mikel Landajuela, Chak Shing Lee, Jiachen Yang, Ruben Glatt, Cláudio P. Santiago, Ignacio Aravena, Terrell Nathan Mundhenk, Garrett Mulcahy, Brenden K. Petersen:
A Unified Framework for Deep Symbolic Regression. NeurIPS 2022- 2021
- [c4]Brenden K. Petersen, Mikel Landajuela, T. Nathan Mundhenk, Cláudio Prata Santiago, Sookyung Kim, Joanne Taery Kim:
Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients. ICLR 2021 - [c3]Mikel Landajuela, Brenden K. Petersen, Sookyung Kim, Cláudio P. Santiago, Ruben Glatt, T. Nathan Mundhenk, Jacob F. Pettit, Daniel M. Faissol:
Discovering symbolic policies with deep reinforcement learning. ICML 2021: 5979-5989 - [c2]T. Nathan Mundhenk, Mikel Landajuela, Ruben Glatt, Cláudio P. Santiago, Daniel M. Faissol, Brenden K. Petersen:
Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding. NeurIPS 2021: 24912-24923 - [i4]Mikel Landajuela, Brenden K. Petersen, Soo K. Kim, Cláudio P. Santiago, Ruben Glatt, T. Nathan Mundhenk, Jacob F. Pettit, Daniel M. Faissol:
Improving exploration in policy gradient search: Application to symbolic optimization. CoRR abs/2107.09158 (2021) - [i3]Brenden K. Petersen, Cláudio P. Santiago, Mikel Landajuela:
Incorporating domain knowledge into neural-guided search. CoRR abs/2107.09182 (2021) - [i2]T. Nathan Mundhenk, Mikel Landajuela, Ruben Glatt, Cláudio P. Santiago, Daniel M. Faissol, Brenden K. Petersen:
Symbolic Regression via Neural-Guided Genetic Programming Population Seeding. CoRR abs/2111.00053 (2021)
2010 – 2019
- 2019
- [j3]Cláudio P. Santiago, Sérgio Assunção Monteiro
, Helder Inácio, Nelson Maculan, Maria Helena Jardim:
An efficient algorithm for the projection of a point on the intersection of two hyperplanes and a box in \(\mathbb {R}^n\). EURO J. Comput. Optim. 7(2): 177-207 (2019) - [j2]Brenden K. Petersen, Jiachen Yang, Will S. Grathwohl, Chase Cockrell, Claudio Santiago, Gary An, Daniel M. Faissol:
Deep Reinforcement Learning and Simulation as a Path Toward Precision Medicine. J. Comput. Biol. 26(6): 597-604 (2019) - 2018
- [j1]Cláudio P. Santiago, Carlile Lavor, Sérgio Assunção Monteiro, Alberto Krone-Martins:
A new algorithm for the small-field astrometric point-pattern matching problem. J. Glob. Optim. 72(1): 55-70 (2018) - [i1]Brenden K. Petersen, Jiachen Yang, Will S. Grathwohl, Chase Cockrell, Claudio Santiago, Gary An, Daniel M. Faissol:
Precision medicine as a control problem: Using simulation and deep reinforcement learning to discover adaptive, personalized multi-cytokine therapy for sepsis. CoRR abs/1802.10440 (2018) - 2016
- [c1]Richard Wheeler, Daniel M. Faissol, Claudio Santiago, Thomas Baginski, Karl Nelson:
Physics and optimal routing for urban radiation source search. MFI 2016: 379-383
2000 – 2009
- 2009
- [b1]Cláudio P. Santiago:
On the nonnegative least squares. Georgia Institute of Technology, Atlanta, GA, USA, 2009
Coauthor Index
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