Ruben Glatt

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 24

Top Topics

Symbolic Regression

Reinforcement Learning

Top Venues

Publications

Donté Harris, Felipe Leno da Silva, Wencong Su, Ruben Glatt
A Review on Simulation Platforms for Agent-Based Modeling in Electrified Transportation. IEEE Trans. Intell. Transp. Syst. 25 (2) (2024)
Hongjun Choi, Jayaraman J. Thiagarajan, Ruben Glatt, Shusen Liu
Enhancing Accuracy and Parameter-Efficiency of Neural Representations for Network Parameterization. CoRR (2024)
Van-Hai Bui, Fangyuan Chang, Wencong Su, Mengqi Wang, Yi Lu Murphey, Felipe Leno da Silva, Can Huang, Lingxiao Xue, Ruben Glatt
Deep Reinforcement Learning-Based Optimal Parameter Design of Power Converters. ICNC (2023)
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)
Ruben Glatt, Shusen Liu
Topological Data Analysis Guided Segment Anything Model Prompt Optimization for Zero-Shot Segmentation in Biological Imaging. CoRR (2023)
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)
Van-Hai Bui, Fangyuan Chang, Wencong Su, Mengqi Wang, Yi Lu Murphey, Felipe Leno da Silva, Can Huang, Linxiao Xue, Ruben Glatt
Deep Neural Network-Based Surrogate Model for Optimal Component Sizing of Power Converters Using Deep Reinforcement Learning. IEEE Access 10 (2022)
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 (2021)
Mikel Landajuela Larma, Brenden K. Petersen, Sookyung Kim, Cláudio P. Santiago, Ruben Glatt, T. Nathan Mundhenk, Jacob F. Pettit, Daniel Faissol
Discovering symbolic policies with deep reinforcement learning. ICML (2021)
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)
Ruben Glatt, Felipe Leno da Silva, Braden Soper, William A. Dawson, Edward Rusu, Ryan A. Goldhahn
Collaborative energy demand response with decentralized actor and centralized critic. BuildSys@SenSys (2021)
Mikel Landajuela Larma, 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 (2021)
William A. Dawson, Ruben Glatt, Edward Rusu, Braden C. Soper, Ryan A. Goldhahn
Hybrid Information-driven Multi-agent Reinforcement Learning. CoRR (2021)
Edward Rusu, Ruben Glatt
Abmarl: Connecting Agent-Based Simulations with Multi-Agent Reinforcement Learning. J. Open Source Softw. 6 (64) (2021)
Ruben Glatt, Felipe Leno da Silva, Reinaldo Augusto da Costa Bianchi, Anna Helena Reali Costa
: Deep Case-based Policy Inference for knowledge transfer in Reinforcement Learning. Expert Syst. Appl. 156 (2020)
Jacob F. Pettit, Ruben Glatt, Jonathan R. Donadee, Brenden K. Petersen
Increasing performance of electric vehicles in ride-hailing services using deep reinforcement learning. CoRR (2019)
Felipe Leno da Silva, Ruben Glatt, Anna Helena Reali Costa
MOO-MDP: An Object-Oriented Representation for Cooperative Multiagent Reinforcement Learning. IEEE Trans. Cybern. 49 (2) (2019)
Rodrigo Cesar Bonini, Felipe Leno da Silva, Ruben Glatt, Edison Spina, Anna Helena Reali Costa
A Framework to Discover and Reuse Object-Oriented Options in Reinforcement Learning. BRACIS (2018)
Felipe Leno da Silva, Ruben Glatt, Anna Helena Reali Costa
An Advising Framework for Multiagent Reinforcement Learning Systems. AAAI (2017)
Felipe Leno da Silva, Ruben Glatt, Anna Helena Reali Costa
Simultaneously Learning and Advising in Multiagent Reinforcement Learning. AAMAS (2017)
Ruben Glatt, Anna Helena Reali Costa
Policy Reuse in Deep Reinforcement Learning. AAAI (2017)
Ruben Glatt, Anna Helena Reali Costa
Improving Deep Reinforcement Learning with Knowledge Transfer. AAAI (2017)
Felipe Leno da Silva, Ruben Glatt, Anna Helena Reali Costa
Object-Oriented Reinforcement Learning in Cooperative Multiagent Domains. BRACIS (2016)
Ruben Glatt, Felipe Leno da Silva, Anna Helena Reali Costa
Towards Knowledge Transfer in Deep Reinforcement Learning. BRACIS (2016)