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2020 – today
- 2026
[i3]Hongshun Chen, Ryan Zhou, Rujing Zha, Zihan Chen, Wenpan Li, Rowan Rolark, John Patrick Reidy, Jian Cao, Ping Guo, David C. Dunand, Horacio D. Espinosa:
Machine Learning-Driven Creep Law Discovery Across Alloy Compositional Space. CoRR abs/2601.08970 (2026)- 2025
- [j1]Ryan Zhou
, Jaume Bacardit, Alexander Edward Ian Brownlee, Stefano Cagnoni, Martin Fyvie, Giovanni Iacca, John A. W. McCall, Niki van Stein, David Walker, Ting Hu:
Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems. IEEE Trans. Evol. Comput. 29(5): 2213-2228 (2025) - [d1]Brandon Bukowski, Yanqi Huang, Ryan Zhou:
Microkinetic Modeling of Ethylene Formation in Mo/ZSM-5 with Machine Learning Potentials. Zenodo, 2025
- 2024
- [i2]Ryan Zhou, Jaume Bacardit, Alexander E. I. Brownlee, Stefano Cagnoni, Martin Fyvie, Giovanni Iacca, John A. W. McCall, Niki van Stein, David Walker, Ting Hu:
Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems. CoRR abs/2406.07811 (2024) - 2023
- [c4]Ryan Zhou, Ting Hu:
Evolving Better Initializations For Neural Networks With Pruning. GECCO Companion 2023: 703-706 - [c3]Herbie Bradley, Honglu Fan, Theodoros Galanos, Ryan Zhou, Daniel Scott, Joel Lehman:
The OpenELM Library: Leveraging Progress in Language Models for Novel Evolutionary Algorithms. GPTP 2023: 177-201 - [i1]Ryan Zhou, Ting Hu:
Evolutionary approaches to explainable machine learning. CoRR abs/2306.14786 (2023) - 2022
- [c2]Ryan Zhou, Christian Muise, Ting Hu:
Permutation-Invariant Representation of Neural Networks with Neuron Embeddings. EuroGP 2022: 294-308 - 2020
- [c1]Maher Selim, Ryan Zhou, Wenying Feng, Omar Alam:
Reducing error propagation for long term energy forecasting using multivariate prediction. CATA 2020: 161-169
Coauthor Index
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