Reducing error propagation for long term energy forecasting using multivariate prediction. - Maher Selim; Ryan Zhou; Wenying Feng 001; Omar Alam (CATA, 2020)

Permutation-Invariant Representation of Neural Networks with Neuron Embeddings. - Ryan Zhou; Christian Muise; Ting Hu 001 (EuroGP, 2022)

Evolving Better Initializations For Neural Networks With Pruning. - Ryan Zhou; Ting Hu 001 (GECCO Companion, 2023)

The OpenELM Library: Leveraging Progress in Language Models for Novel Evolutionary Algorithms. - Herbie Bradley; Honglu Fan; Theodoros Galanos; Ryan Zhou; Daniel Scott; Joel Lehman (GPTP, 2023)

Evolutionary approaches to explainable machine learning. - Ryan Zhou; Ting Hu 001 (CoRR, 2023)

Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems. - Ryan Zhou; Jaume Bacardit; Alexander E. I. Brownlee; Stefano Cagnoni; Martin Fyvie; Giovanni Iacca; John A. W. McCall; Niki van Stein; David Walker 003; Ting Hu 001 (CoRR, 2024)