Learning Transferable Variation Operators in a Continuous Genetic Algorithm. - Stephen Friess; Peter Tiño; Stefan Menzel; Bernhard Sendhoff; Xin Yao 001 (SSCI, 2019)

Representing Experience in Continuous Evolutionary optimisation through Problem-tailored Search Operators. - Stephen Friess; Peter Tiño; Stefan Menzel; Bernhard Sendhoff; Xin Yao 001 (CEC, 2020)

Improving Sampling in Evolution Strategies Through Mixture-Based Distributions Built from Past Problem Instances. - Stephen Friess; Peter Tiño; Stefan Menzel; Bernhard Sendhoff; Xin Yao 001 (PPSN (1), 2020)

Artificial Neural Networks as Feature Extractors in Continuous Evolutionary Optimization. - Stephen Friess; Peter Tiño; Zhao Xu 001; Stefan Menzel; Bernhard Sendhoff; Xin Yao 001 (IJCNN, 2021)

Predicting CMA-ES Operators as Inductive Biases for Shape Optimization Problems. - Stephen Friess; Peter Tino; Stefan Menzel; Bernhard Sendhoff; Xin Yao 001 (SSCI, 2021)

Spatio-Temporal Activity Recognition for Evolutionary Search Behavior Prediction. - Stephen Friess; Peter Tino; Stefan Menzel; Zhao Xu 001; Bernhard Sendhoff; Xin Yao 001 (IJCNN, 2022)

Inductive biases and metaknowledge representations for search-based optimization. - Stephen Friess (2022)