E-LIB Suche - Ergebnisse für: Kommenda, D

1

SRBench++: Principled Benchmarking of Symbolic Regression W..:

de Franca, F. O. ; Virgolin, M. ; Kommenda, M....
IEEE Transactions on Evolutionary Computation. , 2024

2

Extended melt‐conveying models for single‐screw extruders: ..:

Marschik, Christian ; Roland, Wolfgang ; Kommenda, Michael
Polymer Engineering & Science. 63 (2023) 11 - p. 3639-3656 , 2023

Link: https://doi.org/10.1002/..

3

Symbolic Regression in Materials Science: Discovering Inter..:

, In: Genetic and Evolutionary Computation; Genetic Programming Theory and Practice XIX,

Burlacu, Bogdan ; Kommenda, Michael ; Kronberger, Gabriel.. - p. 1-30 , 2023

Link: https://doi.org/10.1007/..

4

Evolutionary Algorithms for Segment Optimization in Vectori..:

, In: Proceedings of the Companion Conference on Genetic and Evolutionary Computation,

Fleck, Philipp ; Winkler, Stephan ; Kommenda, Michael... - p. 439-442 , 2023

Link: https://dl.acm.org/doi/1..

5

Shape-Constrained Symbolic Regression—Improving Extrapolati..:

Kronberger, G. ; de Franca, F. O. ; Burlacu, B...
Evolutionary Computation. 30 (2022) 1 - p. 75-98 , 2022

Link: https://doi.org/10.1162/..

6

Protocol for the Exercise, Cancer and Cognition – The ECCO-..:

Kiesl, David ; Kuzdas-Sallaberger, Marina ; Fuchs, David...
Frontiers in Neurology. 13 (2022) - p. , 2022

Link: https://doi.org/10.3389/..

7

Extending a physics-based constitutive model using genetic ..:

Kronberger, Gabriel ; Kabliman, Evgeniya ; Kronsteiner, Johannes.
Applications in Engineering Science. 9 (2022) - p. 100080 , 2022

Link: https://doi.org/10.1016/..

8

Symbolic Regression with Fast Function Extraction and Nonli..:

, In: Computer Aided Systems Theory – EUROCAST 2022; Lecture Notes in Computer Science,

Kammerer, Lukas ; Kronberger, Gabriel ; Kommenda, Michael - p. 139-146 , 2022

Link: https://doi.org/10.1007/..

9

Application of Symbolic Regression in Polymer Processing:

, In: 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC),

Roland, Wolfgang ; Kommenda, Michael ; Berger-Weber, Gerald R. - p. 311-318 , 2022

Link: https://doi.org/10.1109/..

10

Grammar-Based Vectorial Genetic Programming for Symbolic Re..:

, In: Genetic and Evolutionary Computation; Genetic Programming Theory and Practice XVIII,

Fleck, Philipp ; Winkler, Stephan ; Kommenda, Michael. - p. 21-43 , 2022

Link: https://doi.org/10.1007/..

11

Differences in aphasia syndromes between progressive supran..:

Ransmayr, Lucia ; Fuchs, Alexandra ; Ransmayr-Tepser, Sibylle...
Journal of Neural Transmission. 129 (2022) 8 - p. 1039-1048 , 2022

Link: https://doi.org/10.1007/..

12

Application of symbolic regression for constitutive modelin..:

Kabliman, Evgeniya ; Kolody, Ana Helena ; Kronsteiner, Johannes..
Applications in Engineering Science. 6 (2021) - p. 100052 , 2021

Link: https://doi.org/10.1016/..

13

Data Aggregation for Reducing Training Data in Symbolic Reg..:

, In: Computer Aided Systems Theory – EUROCAST 2019; Lecture Notes in Computer Science,

Kammerer, Lukas ; Kronberger, Gabriel ; Kommenda, Michael - p. 378-386 , 2020

Link: https://doi.org/10.1007/..

14

Symbolic Regression by Exhaustive Search: Reducing the Sear..:

, In: Genetic Programming Theory and Practice XVII; Genetic and Evolutionary Computation,

Kammerer, Lukas ; Kronberger, Gabriel ; Burlacu, Bogdan... - p. 79-99 , 2020

Link: https://doi.org/10.1007/..

15

Identification of Dynamical Systems Using Symbolic Regressi..:

, In: Computer Aided Systems Theory – EUROCAST 2019; Lecture Notes in Computer Science,

Kronberger, Gabriel ; Kammerer, Lukas ; Kommenda, Michael - p. 370-377 , 2020

Link: https://doi.org/10.1007/..