Elliot Meyerson
Collaborator
Publications
     [Expand to show all 22][Minimize]
Discovering Effective Policies for Land-Use Planning with Neuroevolution 2024
Risto Miikkulainen, Olivier Francon, Daniel Young, Elliot Meyerson, Clemens Schwingshackl, Jacob Bieker, Hugo Cunha, and Babak Hodjat, arXiv:2311.12304 (2024). (A shorter version appeared in the Proceedings of the NeurIPS 2023 Workshop: Tackling Climate Change with Machine Learning).
Evolving Deep Neural Networks 2023
Risto Miikkulainen, Jason Liang, Elliot Meyerson, Aditya Rawal, Dan Fink, Olivier Francon, Bala Raju, Hormoz Shahrzad, Arshak Navruzyan, Nigel Duffy, Babak Hodjat, To Appear In Artificial Intelligence in the Age of Neural Networks and Brain Computing (second edition), R. Kozma, C. Alippi, Y. Choe, and F. Morabito (Eds.), New York, 2023. Elsevier.
Simple Genetic Operators are Universal Approximators of Probability Distributions (and other Advantages of Expressive Encodings) 2022
Elliot Meyerson, Xin Qiu, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 739--748, 2022.
Evaluating Medical Aesthetics Treatments through Evolved Age-Estimation Models 2021
Risto Miikkulainen, Elliot Meyerson, Xin Qiu, Ujjayant Sinha, Raghav Kumar, Karen Hofmann, Yiyang Matt Yan, Michael Ye, Jingyuan Yang, Damon Caiazza, and Stephanie Manson Brown, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1009–1017, 2021.
From Prediction to Prescription: Evolutionary Optimization of Non-Pharmaceutical Interventions in the COVID-19 Pandemic 2021
Risto Miikkulainen, Olivier Francon, Elliot Meyerson, Xin Qiu, Darren Sargent, Elisa Canzani, Babak Hodjat, To Appear In IEEE Transactions on Evolutionary Computation, Vol. 25 (2021), pp. 386-401.
The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings 2021
Elliot Meyerson and Risto Miikkulainen, To Appear In International Conference on Learning Representations, 2021.
Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription 2020
Olivier Francon, Santiago Gonzalez, Babak Hodjat, Elliot Meyerson, Risto Miikkulainen, Xin Qiu, Hormoz Shahrzad, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2020), 2020.
Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel 2020
Xin Qiu, Elliot Meyerson, Risto Miikkulainen, In International Conference on Learning Representations, 2020.
The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings 2020
Elliot Meyerson and Risto Miikkulainen, arxiv:2010.02354 (2020).
Evolutionary Neural AutoML for Deep Learning 2019
Jason Liang, Elliot Meyerson, Babak Hodjat, Dan Fink, Karl Mutch, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2019), pp. 401–409 2019.
Evolving Deep Neural Networks 2019
Risto Miikkulainen, Jason Liang, Elliot Meyerson, Aditya Rawal, Dan Fink, Olivier Francon, Bala Raju, Hormoz Shahrzad, Arshak Navruzyan, Nigel Duffy, and Babak Hodjat, In Artificial Intelligence in the Age of Neural Networks and Brain Computing, Robert Kozma, Cesare Alippi, Yoonsuck Choe, and Francesco Carlo Morabito (Eds.), pp. 293-312 2019. Amsterdam: Elsev...
Flavor-cyber-agriculture: Optimization of plant metabolites in an open-source control environment through surrogate modeling 2019
Arielle J. Johnson, Elliot Meyerson, John de la Parra, Timothy L. Savas, Risto Miikkulainen, Caleb B. Harper, bioRxiv:424226, Vol. (2019).
Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains 2019
Elliot Meyerson and Risto Miikkulainen, In 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), 2019.
Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering 2018
Elliot Meyerson and Risto Miikkulainen, In Proceedings of the Sixth International Conference on Learning Representations (ICLR), Vancouver, Canada 2018.
Discovering Multi-Purpose Modules through Deep Multitask Learning 2018
Elliot Meyerson, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Evolutionary Architecture Search For Deep Multitask Networks 2018
Jason Liang, Elliot Meyerson, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pp. 466–473, Kyoto, Japan, 2018.
Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing---and Back 2018
Elliot Meyerson, Risto Miikkulainen, In Proceedings of the 35th International Conference on Machine Learning, pp. 739-748 2018.
Discovering Evolutionary Stepping Stones through Behavior Domination 2017
Elliot Meyerson and Risto Miikkulainen, To Appear In Proceedings of The Genetic and Evolutionary Computation Conference (GECCO 2017), Berlin, Germany, July 2017. ACM.
Learning Behavior Characterizations for Novelty Search 2016
Elliot Meyerson, Joel Lehman and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2016), Denver, Colorado 2016. ACM.
Reuse of Neural Modules for General Video Game Playing 2016
Alexander Braylan, Mark Hollenbeck, Elliot Meyerson and Risto Miikkulainen, To Appear In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16) 2016.
Frame Skip Is a Powerful Parameter for Learning to Play Atari 2015
Alexander Braylan, Mark Hollenbeck, Elliot Meyerson and Risto Miikkulainen, In AAAI-15 Workshop on Learning for General Competency in Video Games 2015.
On the Cross-Domain Reusability of Neural Modules for General Video Game Playing 2015
Alexander Braylan, Mark Hollenbeck, Elliot Meyerson and Risto Miikkulainen, In IJCAI'15 Workshop on General Intelligence in Game-Playing Agents, pp. 7--14 2015.
Areas of Interest
Cognitive Science Control Evolutionary Computation Game Playing General Game Playing Neuroevolution Robotics
Labs
Currently affiliated with Neural Networks Formerly affiliated with Neural Networks