Ruben Glatt - RankMe

30 papers A* 6A 1Misc 1Journal 17Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Toward Autonomous Laboratory Safety Monitoring with Vision Language Models: Learning to See Hazards Through Scene Structure. CoRR Trishna Chakraborty, Udita Ghosh, Aldair Ernesto Gongora, Ruben Glatt, Yue Dong, Jiachen Li, Amit K. Roy-Chowdhury, Chengyu Song
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	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`	Oracle-RLAIF: An Improved Fine-Tuning Framework for Multi-modal Video Models through Reinforcement Learning from Ranking Feedback. CoRR Derek Shi, Ruben Glatt, Christine Klymko, Shubham Mohole, Hongjun Choi, Shashank Kushwaha, Sam Sakla, Felipe Leno da Silva
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
2025	—	`conf`	VERIRAG: Healthcare Claim Verification via Statistical Audit in Retrieval-Augmented Generation. BCB Shubham Mohole, Hongjun Choi, Shusen Liu, Christine Klymko, Shashank Kushwaha, Derek Shi, Wesam A. Sakla, Sainyam Galhotra, Ruben Glatt
2025	J	`jnl`	VERIRAG: Healthcare Claim Verification via Statistical Audit in Retrieval-Augmented Generation. CoRR Shubham Mohole, Hongjun Choi, Shusen Liu, Christine Klymko, Shashank Kushwaha, Derek Shi, Wesam A. Sakla, Sainyam Galhotra, Ruben Glatt
2024	J	`jnl`	A Review on Simulation Platforms for Agent-Based Modeling in Electrified Transportation. IEEE Trans. Intell. Transp. Syst. Donté Harris, Felipe Leno da Silva, Wencong Su, Ruben Glatt
2024	J	`jnl`	Enhancing Accuracy and Parameter-Efficiency of Neural Representations for Network Parameterization. CoRR Hongjun Choi, Jayaraman J. Thiagarajan, Ruben Glatt, Shusen Liu
2023	Misc	`conf`	Deep Reinforcement Learning-Based Optimal Parameter Design of Power Converters. ICNC Van-Hai Bui, Fangyuan Chang, Wencong Su, Mengqi Wang, Yi Lu Murphey, Felipe Leno da Silva, Can Huang, Lingxiao Xue, Ruben Glatt
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
2023	J	`jnl`	Topological Data Analysis Guided Segment Anything Model Prompt Optimization for Zero-Shot Segmentation in Biological Imaging. CoRR Ruben Glatt, Shusen Liu
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	J	`jnl`	Deep Neural Network-Based Surrogate Model for Optimal Component Sizing of Power Converters Using Deep Reinforcement Learning. IEEE Access Van-Hai Bui, Fangyuan Chang, Wencong Su, Mengqi Wang, Yi Lu Murphey, Felipe Leno da Silva, Can Huang, Lingxiao Xue, Ruben Glatt
2021	J	`jnl`	Abmarl: Connecting Agent-Based Simulations with Multi-Agent Reinforcement Learning. J. Open Source Softw. Edward Rusu, Ruben Glatt
2021	—	`conf`	Collaborative energy demand response with decentralized actor and centralized critic. BuildSys Ruben Glatt, Felipe Leno da Silva, Braden Soper, William A. Dawson, Edward Rusu, Ryan A. Goldhahn
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`	Hybrid Information-driven Multi-agent Reinforcement Learning. CoRR William A. Dawson, Ruben Glatt, Edward Rusu, Braden C. Soper, Ryan A. Goldhahn
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	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
2019	J	`jnl`	Increasing performance of electric vehicles in ride-hailing services using deep reinforcement learning. CoRR Jacob F. Pettit, Ruben Glatt, Jonathan R. Donadee, Brenden K. Petersen
2019	J	`jnl`	MOO-MDP: An Object-Oriented Representation for Cooperative Multiagent Reinforcement Learning. IEEE Trans. Cybern. Felipe Leno da Silva, Ruben Glatt, Anna Helena Reali Costa
2018	—	`conf`	A Framework to Discover and Reuse Object-Oriented Options in Reinforcement Learning. BRACIS Rodrigo Cesar Bonini, Felipe Leno da Silva, Ruben Glatt, Edison Spina, Anna Helena Reali Costa
2017	A*	`conf`	An Advising Framework for Multiagent Reinforcement Learning Systems. AAAI Felipe Leno da Silva, Ruben Glatt, Anna Helena Reali Costa
2017	A*	`conf`	Improving Deep Reinforcement Learning with Knowledge Transfer. AAAI Ruben Glatt, Anna Helena Reali Costa
2017	A*	`conf`	Policy Reuse in Deep Reinforcement Learning. AAAI Ruben Glatt, Anna Helena Reali Costa
2017	A	`conf`	Simultaneously Learning and Advising in Multiagent Reinforcement Learning. AAMAS Felipe Leno da Silva, Ruben Glatt, Anna Helena Reali Costa
2016	—	`conf`	Object-Oriented Reinforcement Learning in Cooperative Multiagent Domains. BRACIS Felipe Leno da Silva, Ruben Glatt, Anna Helena Reali Costa
2016	—	`conf`	Towards Knowledge Transfer in Deep Reinforcement Learning. BRACIS Ruben Glatt, Felipe Leno da Silva, Anna Helena Reali Costa