Lukas Kammerer

According to our database, Lukas Kammerer authored at least 9 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

A precise symbolic emulator of the linear matter power spectrum.

Deaglan J. Bartlett, Lukas Kammerer, Gabriel Kronberger, Harry Desmond, Pedro G. Ferreira, Benjamin D. Wandelt, Bogdan Burlacu, David Alonso, Matteo Zennaro

CoRR, 2023

2022

Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization.

Lukas Kammerer, Gabriel Kronberger, Michael Kommenda

Proceedings of the Computer Aided Systems Theory - EUROCAST 2022, 2022

2021

Empirical analysis of variance for genetic programming based symbolic regression.

Lukas Kammerer, Gabriel Kronberger, Stephan M. Winkler

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

2019

Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication.

Lukas Kammerer, Gabriel Kronberger, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller

Proceedings of the Genetic Programming Theory and Practice XVII [GPTP 2019, 2019

Identification of Dynamical Systems Using Symbolic Regression.

Gabriel Kronberger, Lukas Kammerer, Michael Kommenda

Proceedings of the Computer Aided Systems Theory - EUROCAST 2019, 2019

Data Aggregation for Reducing Training Data in Symbolic Regression.

Lukas Kammerer, Gabriel Kronberger, Michael Kommenda

Proceedings of the Computer Aided Systems Theory - EUROCAST 2019, 2019

Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression.

Bogdan Burlacu, Lukas Kammerer, Michael Affenzeller, Gabriel Kronberger

Proceedings of the Computer Aided Systems Theory - EUROCAST 2019, 2019

2018

Cluster Analysis of a Symbolic Regression Search Space.

Gabriel Kronberger, Lukas Kammerer, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller

Proceedings of the Genetic Programming Theory and Practice XVI, 2018

Confidence-based ensemble modeling in medical data mining.

Lukas Kammerer, Michael Affenzeller

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018