Multi-Robot Foremost Coverage of Time-Varying Graphs. - Eric Aaron; Danny Krizanc; Elliot Meyerson (ALGOSENSORS, 2014)

DMVP: Foremost Waypoint Coverage of Time-Varying Graphs. - Eric Aaron; Danny Krizanc; Elliot Meyerson (WG, 2014)

Frame Skip Is a Powerful Parameter for Learning to Play Atari. - Alexander Braylan; Mark Hollenbeck; Elliot Meyerson; Risto Miikkulainen (AAAI Workshop: Learning for General Competency in Video Games, 2015)

On the Cross-Domain Reusability of Neural Modules for General Video Game Playing. - Alexander Braylan; Mark Hollenbeck; Elliot Meyerson; Risto Miikkulainen (CGW/GIGA@IJCAI, 2015)

Reuse of Neural Modules for General Video Game Playing. - Alexander Braylan; Mark Hollenbeck; Elliot Meyerson; Risto Miikkulainen (AAAI, 2016)

Learning Behavior Characterizations for Novelty Search. - Elliot Meyerson; Joel Lehman; Risto Miikkulainen (GECCO, 2016)

Discovering evolutionary stepping stones through behavior domination. - Elliot Meyerson; Risto Miikkulainen (GECCO, 2017)

Evolving Deep Neural Networks. - Risto Miikkulainen; Jason Zhi Liang; Elliot Meyerson; Aditya Rawal; Daniel Fink 003; Olivier Francon; Bala Raju; Hormoz Shahrzad; Arshak Navruzyan; Nigel Duffy; Babak Hodjat (CoRR, 2017)

Evolutionary architecture search for deep multitask networks. - Jason Zhi Liang; Elliot Meyerson; Risto Miikkulainen (GECCO, 2018)

Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering. - Elliot Meyerson; Risto Miikkulainen (ICLR (Poster), 2018)

Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing-and Back. - Elliot Meyerson; Risto Miikkulainen (ICML, 2018)

Evolutionary neural AutoML for deep learning. - Jason Zhi Liang; Elliot Meyerson; Babak Hodjat; Daniel Fink 003; Karl Mutch; Risto Miikkulainen (GECCO, 2019)

Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains. - Elliot Meyerson; Risto Miikkulainen (NeurIPS, 2019)

Effective reinforcement learning through evolutionary surrogate-assisted prescription. - Olivier Francon; Santiago Gonzalez; Babak Hodjat; Elliot Meyerson; Risto Miikkulainen; Xin Qiu 001; Hormoz Shahrzad (GECCO, 2020)

Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel. - Xin Qiu 001; Elliot Meyerson; Risto Miikkulainen (ICLR, 2020)

From Prediction to Prescription: AI-Based Optimization of Non-Pharmaceutical Interventions for the COVID-19 Pandemic. - Risto Miikkulainen; Olivier Francon; Elliot Meyerson; Xin Qiu 001; Elisa Canzani; Babak Hodjat (CoRR, 2020)

Evaluating medical aesthetics treatments through evolved age-estimation models. - Risto Miikkulainen; Elliot Meyerson; Xin Qiu 001; Ujjayant Sinha; Raghav Kumar; Karen Hofmann; Yiyang Matt Yan; Michael Ye; Jingyuan Yang 003; Damon Caiazza; Stephanie Manson Brown (GECCO, 2021)

The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings. - Elliot Meyerson; Risto Miikkulainen (ICLR, 2021)

From Prediction to Prescription: Evolutionary Optimization of Nonpharmaceutical Interventions in the COVID-19 Pandemic. - Risto Miikkulainen; Olivier Francon; Elliot Meyerson; Xin Qiu 001; Darren Sargent; Elisa Canzani; Babak Hodjat (IEEE Trans. Evol. Comput., 2021)

Simple genetic operators are universal approximators of probability distributions (and other advantages of expressive encodings). - Elliot Meyerson; Xin Qiu 001; Risto Miikkulainen (GECCO, 2022)

Discovering Effective Policies for Land-Use Planning. - Risto Miikkulainen; Olivier Francon; Daniel Young; Elliot Meyerson; Babak Hodjat (CoRR, 2023)

Unlocking the Potential of Global Human Expertise. - Elliot Meyerson; Olivier Francon; Darren Sargent; Babak Hodjat; Risto Miikkulainen (NeurIPS, 2024)

From Text to Life: On the Reciprocal Relationship between Artificial Life and Large Language Models. - Eleni Nisioti; Claire Glanois; Elias Najarro; Andrew Dai 001; Elliot Meyerson; Joachim Winther Pedersen; Laetitia Teodorescu; Conor F. Hayes; Shyam Sudhakaran; Sebastian Risi (CoRR, 2024)

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models. - Alex Havrilla; Andrew Dai 001; Laura O'Mahony; Koen Oostermeijer; Vera Zisler; Alon Albalak; Fabrizio Milo; Sharath Chandra Raparthy; Kanishk Gandhi; Baber Abbasi; Duy Phung; Maia Iyer; et al. (CoRR, 2024)

Language Model Crossover: Variation through Few-Shot Prompting. - Elliot Meyerson; Mark J. Nelson; Herbie Bradley; Adam Gaier; Arash Moradi Karkaj; Amy K. Hoover; Joel Lehman (ACM Trans. Evol. Learn. Optim., 2024)

Evolution and The Knightian Blindspot of Machine Learning. - Joel Lehman; Elliot Meyerson; Tarek El-Gaaly; Kenneth O. Stanley; Tarin Ziyaee (CoRR, 2025)

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives. - Elliot Meyerson; Xin Qiu 001 (CoRR, 2025)