default search action
Gabriel Kronberger
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [j12]Florian Bachinger
, Lisa Ehrlinger
Data Validation Utilizing Expert Knowledge and Shape Constraints. ACM J. Data Inf. Qual. 16(2): 13:1-13:27 (2024) - [j11]Daniel Parra
Learning Difference Equations With Structured Grammatical Evolution for Postprandial Glycaemia Prediction. IEEE J. Biomed. Health Informatics 28(5): 3067-3078 (2024) - [c73]Patrick E. Leser
Comparing Methods for Estimating Marginal Likelihood in Symbolic Regression. GECCO Companion 2024: 2058-2066 - [c72]Gabriel Kronberger
The Inefficiency of Genetic Programming for Symbolic Regression. PPSN (1) 2024: 273-289 - [i30]Gabriel Kronberger, Fabrício Olivetti de França, Harry Desmond, Deaglan J. Bartlett
The Inefficiency of Genetic Programming for Symbolic Regression - Extended Version. CoRR abs/2404.17292 (2024) - [i29]Yousef A. Radwan, Gabriel Kronberger, Stephan M. Winkler:
A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming. CoRR abs/2406.03585 (2024) - 2023
- [j10]Christian Haider
Shape-constrained multi-objective genetic programming for symbolic regression. Appl. Soft Comput. 132: 109855 (2023) - [c71]Fabrício Olivetti de França
Reducing Overparameterization of Symbolic Regression Models with Equality Saturation. GECCO 2023: 1064-1072 - [c70]Christian Haider, Fabrício Olivetti de França, Bogdan Burlacu, Florian Bachinger, Gabriel Kronberger, Michael Affenzeller:
Shape-constrained Symbolic Regression: Real-World Applications in Magnetization, Extrusion and Data Validation. GPTP 2023: 225-240 - [c69]Hannah Janout, Thomas Paier, Carina Ringelhahn, Michael Heckmann, Andreas Haghofer, Gabriel Kronberger, Stephan Winkler
Identification of Surrogate Models for the Prediction of Degrees of Freedom within a Tolerance Chain. ISM 2023: 796-805 - [i28]Daniel Parra, David Joedicke, J. Manuel Velasco, Gabriel Kronberger, José Ignacio Hidalgo:
Learning Difference Equations with Structured Grammatical Evolution for Postprandial Glycaemia Prediction. CoRR abs/2307.01238 (2023) - [i27]Deaglan J. Bartlett, Lukas Kammerer, Gabriel Kronberger, Harry Desmond, Pedro G. Ferreira, Benjamin D. Wandelt, Bogdan Burlacu, David Alonso, Matteo Zennaro:
A precise symbolic emulator of the linear matter power spectrum. CoRR abs/2311.15865 (2023) - 2022
- [j9]Gabriel Kronberger, Fabrício Olivetti de França, Bogdan Burlacu, Christian Haider, Michael Kommenda:
Shape-Constrained Symbolic Regression - Improving Extrapolation with Prior Knowledge. Evol. Comput. 30(1): 75-98 (2022) - [c68]Lukas Kammerer
Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization. EUROCAST 2022: 139-146 - [c67]Florian Bachinger
Comparing Shape-Constrained Regression Algorithms for Data Validation. EUROCAST 2022: 147-154 - [c66]Christian Haider, Gabriel Kronberger:
Shape-Constrained Symbolic Regression with NSGA-III. EUROCAST 2022: 164-172 - [c65]David Joedicke
Identifying Differential Equations for the Prediction of Blood Glucose using Sparse Identification of Nonlinear Systems. EUROCAST 2022: 181-188 - [c64]Christian Haider, Fabrício Olivetti de França, Gabriel Kronberger, Bogdan Burlacu:
Comparing optimistic and pessimistic constraint evaluation in shape-constrained symbolic regression. GECCO 2022: 938-945 - [c63]Bogdan Burlacu, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller:
Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data. GPTP 2022: 1-30 - [c62]Martin Steiger, Hans Georg Brachtendorf, Gabriel Kronberger:
Identification of Discrete Non-Linear Dynamics of a Radio-Frequency Power Amplifier Circuit using Symbolic Regression. SYNASC 2022: 297-303 - [c61]Gabriel Kronberger:
Local Optimization Often is Ill-conditioned in Genetic Programming for Symbolic Regression. SYNASC 2022: 304-310 - [c60]David Piringer, Bernhard Bloder, Gabriel Kronberger:
Steel Phase Kinetics Modeling using Symbolic Regression. SYNASC 2022: 327-330 - [i26]Bogdan Burlacu, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler
Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data. CoRR abs/2206.06422 (2022) - [i25]Gabriel Kronberger:
Local Optimization Often is Ill-conditioned in Genetic Programming for Symbolic Regression. CoRR abs/2209.00942 (2022) - [i24]Fabrício Olivetti de França, Gabriel Kronberger:
Prediction Intervals and Confidence Regions for Symbolic Regression Models based on Likelihood Profiles. CoRR abs/2209.06454 (2022) - [i23]Florian Bachinger, Gabriel Kronberger:
Comparing Shape-Constrained Regression Algorithms for Data Validation. CoRR abs/2209.09602 (2022) - [i22]Lukas Kammerer, Gabriel Kronberger, Michael Kommenda:
Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization. CoRR abs/2209.09675 (2022) - [i21]David Jödicke, Daniel Parra, Gabriel Kronberger, Stephan M. Winkler
Identifying Differential Equations to predict Blood Glucose using Sparse Identification of Nonlinear Systems. CoRR abs/2209.13852 (2022) - [i20]David Piringer, Bernhard Bloder, Gabriel Kronberger:
Steel Phase Kinetics Modeling using Symbolic Regression. CoRR abs/2212.10284 (2022) - 2021
- [c59]Laura Millán
Estimation of Grain-Level Residual Stresses in a Quenched Cylindrical Sample of Aluminum Alloy AA5083 Using Genetic Programming. EvoApplications 2021: 421-436 - [c58]Lukas Kammerer, Gabriel Kronberger, Stephan M. Winkler:
Empirical analysis of variance for genetic programming based symbolic regression. GECCO Companion 2021: 251-252 - [i19]Gabriel Kronberger, Fabrício Olivetti de França, Bogdan Burlacu, Christian Haider, Michael Kommenda:
Shape-constrained Symbolic Regression - Improving Extrapolation with Prior Knowledge. CoRR abs/2103.15624 (2021) - [i18]Gabriel Kronberger, Lukas Kammerer, Michael Kommenda:
Identification of Dynamical Systems using Symbolic Regression. CoRR abs/2107.06131 (2021) - [i17]Christian Haider, Fabrício Olivetti de França, Bogdan Burlacu, Gabriel Kronberger:
Using Shape Constraints for Improving Symbolic Regression Models. CoRR abs/2107.09458 (2021) - [i16]Gabriel Kronberger, Michael Kommenda, Andreas Promberger, Falk Nickel:
Predicting Friction System Performance with Symbolic Regression and Genetic Programming with Factor Variables. CoRR abs/2107.09484 (2021) - [i15]Bogdan Burlacu, Lukas Kammerer, Michael Affenzeller, Gabriel Kronberger:
Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression. CoRR abs/2107.10640 (2021) - [i14]Florian Bachinger, Gabriel Kronberger:
Concept for a Technical Infrastructure for Management of Predictive Models in Industrial Applications. CoRR abs/2107.13821 (2021) - [i13]Gabriel Kronberger, Evgeniya Kabliman, Johannes Kronsteiner, Michael Kommenda:
Predicting Calibration Parameter Values for Constitutive Models using Genetic Programming. CoRR abs/2108.01595 (2021) - [i12]Jan Zenisek, Gabriel Kronberger, Josef Wolfartsberger, Norbert Wild, Michael Affenzeller:
Concept Drift Detection with Variable Interaction Networks. CoRR abs/2108.03273 (2021) - [i11]Erik Pitzer, Gabriel Kronberger:
Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-valued Optimization Problem. CoRR abs/2108.03274 (2021) - [i10]Lukas Kammerer, Gabriel Kronberger, Michael Kommenda:
Data Aggregation for Reducing Training Data in Symbolic Regression. CoRR abs/2108.10660 (2021) - [i9]Michael Kommenda, Andreas Beham, Michael Affenzeller, Gabriel Kronberger:
Complexity Measures for Multi-objective Symbolic Regression. CoRR abs/2109.00238 (2021) - [i8]Lukas Kammerer, Gabriel Kronberger, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller:
Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication. CoRR abs/2109.13895 (2021) - [i7]Gabriel Kronberger, Lukas Kammerer, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller:
Cluster Analysis of a Symbolic Regression Search Space. CoRR abs/2109.13898 (2021) - [i6]Michael Kommenda, Johannes Karder, Andreas Beham, Bogdan Burlacu, Gabriel Kronberger, Stefan Wagner, Michael Affenzeller:
Optimization Networks for Integrated Machine Learning. CoRR abs/2110.00415 (2021) - 2020
- [j8]Michael Kommenda
Parameter identification for symbolic regression using nonlinear least squares. Genet. Program. Evolvable Mach. 21(3): 471-501 (2020) - [j7]Gabriel Kronberger
Multilayer analysis of population diversity in grammatical evolution for symbolic regression. Soft Comput. 24(15): 11283-11295 (2020) - [c57]David Joedicke, Gabriel Kronberger, José Manuel Colmenar, Stephan M. Winkler, José Manuel Velasco, Sergio Contador, José Ignacio Hidalgo:
Analysis of the performance of Genetic Programming on the Blood Glucose Level Prediction Challenge 2020. KDH@ECAI 2020: 141-145 - [c56]Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda:
Operon C++: an efficient genetic programming framework for symbolic regression. GECCO Companion 2020: 1562-1570
2010 – 2019
- 2019
- [c55]Stefan Prieschl, Dominic Girardi
Using Ontologies to Express Prior Knowledge for Genetic Programming. CD-MAKE 2019: 362-376 - [c54]Bogdan Burlacu
Online Diversity Control in Symbolic Regression via a Fast Hash-based Tree Similarity Measure. CEC 2019: 2175-2182 - [c53]Florian Bachinger
Concept for a Technical Infrastructure for Management of Predictive Models in Industrial Applications. EUROCAST (1) 2019: 263-270 - [c52]Jan Zenisek, Gabriel Kronberger, Josef Wolfartsberger, Norbert Wild, Michael Affenzeller
Concept Drift Detection with Variable Interaction Networks. EUROCAST (1) 2019: 296-303 - [c51]Bogdan Burlacu
Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression. EUROCAST (1) 2019: 361-369 - [c50]Gabriel Kronberger
Identification of Dynamical Systems Using Symbolic Regression. EUROCAST (1) 2019: 370-377 - [c49]Lukas Kammerer
Data Aggregation for Reducing Training Data in Symbolic Regression. EUROCAST (1) 2019: 378-386 - [c48]Bogdan Burlacu
Parsimony measures in multi-objective genetic programming for symbolic regression. GECCO (Companion) 2019: 338-339 - [c47]Lukas Kammerer, Gabriel Kronberger, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller:
Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication. GPTP 2019: 79-99 - [i5]Bogdan Burlacu, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda:
Online Diversity Control in Symbolic Regression via a Fast Hash-based Tree Similarity Measure. CoRR abs/1902.00882 (2019) - 2018
- [j6]Gabriel Kronberger
Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems. Appl. Soft Comput. 69: 610-624 (2018) - [c46]Gabriel Kronberger
Predicting friction system performance with symbolic regression and genetic programming with factor variables. GECCO 2018: 1278-1285 - [c45]Gabriel Kronberger, Lukas Kammerer, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller:
Cluster Analysis of a Symbolic Regression Search Space. GPTP 2018: 85-102 - [p6]José Ignacio Hidalgo, J. Manuel Colmenar, J. Manuel Velasco, Gabriel Kronberger, Stephan M. Winkler
Identification of Models for Glucose Blood Values in Diabetics by Grammatical Evolution. Handbook of Grammatical Evolution 2018: 367-393 - 2017
- [j5]José Ignacio Hidalgo
Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods. J. Medical Syst. 41(9): 142 (2017) - [c44]Gabriel Kronberger
Measures for the Evaluation and Comparison of Graphical Model Structures. EUROCAST (1) 2017: 283-290 - [c43]Michael Kommenda
Optimization Networks for Integrated Machine Learning. EUROCAST (1) 2017: 392-399 - [c42]Michael Affenzeller
Offspring Selection Genetic Algorithm Revisited: Improvements in Efficiency by Early Stopping Criteria in the Evaluation of Unsuccessful Individuals. EUROCAST (1) 2017: 424-431 - [c41]Bogdan Burlacu
Analysis of Schema Frequencies in Genetic Programming. EUROCAST (1) 2017: 432-438 - [c40]José Ignacio Hidalgo, J. Manuel Colmenar, Gabriel Kronberger
Glucose Prognosis by Grammatical Evolution. EUROCAST (1) 2017: 455-463 - [c39]Michael Affenzeller
Dynamic observation of genotypic and phenotypic diversity for different symbolic regression GP variants. GECCO (Companion) 2017: 1553-1558 - [c38]Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler:
Schema Analysis in Tree-Based Genetic Programming. GPTP 2017: 17-37 - 2016
- [j4]Stephan M. Winkler, Bonifacio Castaño, Sergio Luengo-Sanchez, Susanne Schaller, Gabriel Kronberger, Michael Affenzeller:
Heterogeneous model ensembles for short-term prediction of stock market trends. Int. J. Simul. Process. Model. 11(6): 504-513 (2016) - [c37]J. Manuel Colmenar, Stephan M. Winkler
Predicting Glycemia in Diabetic Patients By Evolutionary Computation and Continuous Glucose Monitoring. GECCO (Companion) 2016: 1393-1400 - [c36]Stephan M. Winkler, Michael Affenzeller, Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda, Philipp Fleck:
Similarity-Based Analysis of Population Dynamics in Genetic Programming Performing Symbolic Regression. GPTP 2016: 1-17 - [c35]Edwin Lughofer, Gabriel Kronberger, Michael Kommenda, Susanne Saminger-Platz, Andreas Promberger, Falk Nickel, Stephan M. Winkler
Robust Fuzzy Modeling and Symbolic Regression for Establishing Accurate and Interpretable Prediction Models in Supervising Tribological Systems. IJCCI (FCTA) 2016: 51-63 - 2015
- [c34]Stephan M. Winkler
Dynamics of Predictability and Variable Influences Identified in Financial Data Using Sliding Window Machine Learning. EUROCAST 2015: 326-333 - [c33]Erik Pitzer, Gabriel Kronberger
Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-Valued Optimization Problem. EUROCAST 2015: 375-383 - [c32]Michael Kommenda
Complexity Measures for Multi-objective Symbolic Regression. EUROCAST 2015: 409-416 - [c31]Gabriel Kronberger
Using Contextual Information in Sequential Search for Grammatical Optimization Problems. EUROCAST 2015: 417-424 - [c30]Michael Kommenda, Gabriel Kronberger, Michael Affenzeller, Stephan M. Winkler, Bogdan Burlacu:
Evolving Simple Symbolic Regression Models by Multi-Objective Genetic Programming. GPTP 2015: 1-19 - [p5]Bogdan Burlacu
Methods for Genealogy and Building Block Analysis in Genetic Programming. Computational Intelligence and Efficiency in Engineering Systems 2015: 61-74 - [p4]Michael Kommenda
Multi-Population Genetic Programming with Data Migration for Symbolic Regression. Computational Intelligence and Efficiency in Engineering Systems 2015: 75-87 - [p3]Gabriel Kronberger
Search Strategies for Grammatical Optimization Problems - Alternatives to Grammar-Guided Genetic Programming. Computational Intelligence and Efficiency in Engineering Systems 2015: 89-102 - [p2]Erik Pitzer, Gabriel Kronberger
Concise Supply-Chain Simulation Optimization for Large Scale Logistic Networks. Computational Intelligence and Efficiency in Engineering Systems 2015: 429-442 - 2014
- [j3]Gerd Bramerdorfer, Stephan M. Winkler
Using FE Calculations and Data-Based System Identification Techniques to Model the Nonlinear Behavior of PMSMs. IEEE Trans. Ind. Electron. 61(11): 6454-6462 (2014) - [c29]Andreas Beham
Scripting and framework integration in heuristic optimization environments. GECCO (Companion) 2014: 1109-1116 - [c28]Michael Kommenda
Genetic programming with data migration for symbolic regression. GECCO (Companion) 2014: 1361-1366 - [c27]Stephan M. Winkler, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda, Bogdan Burlacu, Stefan Wagner:
Sliding Window Symbolic Regression for Detecting Changes of System Dynamics. GPTP 2014: 91-107 - 2013
- [j2]David Robert White, James McDermott, Mauro Castelli
Better GP benchmarks: community survey results and proposals. Genet. Program. Evolvable Mach. 14(1): 3-29 (2013) - [j1]Stephan M. Winkler
On the use of estimated tumour marker classifications in tumour diagnosis prediction - a case study for breast cancer. Int. J. Simul. Process. Model. 8(1): 29-41 (2013) - [c26]Gabriel Kronberger:
Declarative Modeling and Bayesian Inference of Dark Matter Halos. EUROCAST (1) 2013: 195-202 - [c25]Gabriel Kronberger, Michael Kommenda:
Evolution of Covariance Functions for Gaussian Process Regression Using Genetic Programming. EUROCAST (1) 2013: 308-315 - [c24]Michael Kommenda, Michael Affenzeller, Gabriel Kronberger, Stephan M. Winkler
Nonlinear Least Squares Optimization of Constants in Symbolic Regression. EUROCAST (1) 2013: 420-427 - [c23]Michael Kommenda
Effects of constant optimization by nonlinear least squares minimization in symbolic regression. GECCO (Companion) 2013: 1121-1128 - [c22]Gabriel Kronberger
GPDL: a framework-independent problem definition language for grammar-guided genetic programming. GECCO (Companion) 2013: 1333-1340 - [c21]Bogdan Burlacu
Visualization of genetic lineages and inheritance information in genetic programming. GECCO (Companion) 2013: 1351-1358 - [c20]Michael Affenzeller, Stephan M. Winkler, Gabriel Kronberger, Michael Kommenda, Bogdan Burlacu, Stefan Wagner:
Gaining Deeper Insights in Symbolic Regression. GPTP 2013: 175-190 - [i4]Gabriel Kronberger, Michael Kommenda:
Evolution of Covariance Functions for Gaussian Process Regression using Genetic Programming. CoRR abs/1305.3794 (2013) - [i3]Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller, Andreas Beham, Stefan Wagner:
On the Success Rate of Crossover Operators for Genetic Programming with Offspring Selection. CoRR abs/1309.5896 (2013) - [i2]Michael Kommenda, Gabriel Kronberger, Christoph Feilmayr, Michael Affenzeller:
Data Mining using Unguided Symbolic Regression on a Blast Furnace Dataset. CoRR abs/1309.5931 (2013) - 2012
- [c19]Mathieu d'Aquin, Gabriel Kronberger, Mari Carmen Suárez-Figueroa:
Combining Data Mining and Ontology Engineering to Enrich Ontologies and Linked Data. KNOW@LOD 2012: 19-24 - [c18]Michael Kommenda
On the architecture and implementation of tree-based genetic programming in HeuristicLab. GECCO (Companion) 2012: 101-108 - [c17]Stefan Wagner
Algorithm and experiment design with heuristic lab: an open source optimization environment for research and education. GECCO (Companion) 2012: 1287-1316 - [c16]Gabriel Kronberger
Knowledge Discovery through Symbolic Regression with HeuristicLab. ECML/PKDD (2) 2012: 824-827 - [i1]Gabriel Kronberger, Stefan Fink, Michael Kommenda, Michael Affenzeller:
Macro-Economic Time Series Modeling and Interaction Networks. CoRR abs/1212.2044 (2012) - 2011
- [c15]Alexandru-Ciprian Zavoianu
Improving the Parsimony of Regression Models for an Enhanced Genetic Programming Process. EUROCAST (1) 2011: 264-271 - [c14]Stephan M. Winkler
Analysis of Selected Evolutionary Algorithms in Feature Selection and Parameter Optimization for Data Based Tumor Marker Modeling. EUROCAST (1) 2011: 335-342 - [c13]Christoph Neumüller, Stefan Wagner
Parameter Meta-optimization of Metaheuristic Optimization Algorithms. EUROCAST (1) 2011: 367-374 - [c12]Michael Kommenda
Application of Symbolic Regression on Blast Furnace and Temper Mill Datasets. EUROCAST (1) 2011: 400-407 - [c11]Gabriel Kronberger
Market Basket Analysis of Retail Data: Supervised Learning Approach. EUROCAST (1) 2011: 464-471 - [c10]Gabriel Kronberger
Macro-economic Time Series Modeling and Interaction Networks. EvoApplications (2) 2011: 101-110 - [c9]Michael Kommenda
Data Mining Using Unguided Symbolic Regression on a Blast Furnace Dataset. EvoApplications (1) 2011: 274-283 - [c8]Gabriel Kronberger
Overfitting detection and adaptive covariant parsimony pressure for symbolic regression. GECCO (Companion) 2011: 631-638 - [c7]Stefan Wagner
Algorithm and experiment design with heuristiclab: an open source optimization environment for research and education. GECCO (Companion) 2011: 1411-1438
2000 – 2009
- 2009
- [c6]Stefan Wagner
Model Driven Rapid Prototyping of Heuristic Optimization Algorithms. EUROCAST 2009: 729-736 - [c5]Gabriel Kronberger
On the Success Rate of Crossover Operators for Genetic Programming with Offspring Selection. EUROCAST 2009: 793-800 - [c4]Monika Kofler, Stefan Wagner
Priority Rule Generation with a Genetic Algorithm to Minimize Sequence Dependent Setup Costs. EUROCAST 2009: 817-824 - [c3]Gabriel Kronberger
On Crossover Success Rate in Genetic Programming with Offspring Selection. EuroGP 2009: 232-243 - [p1]Michael Affenzeller
Metaheuristic Optimization. Hagenberg Research 2009: 103-155 - 2007
- [c2]Stefan Wagner, Stephan M. Winkler
Benefits of Plugin-Based Heuristic Optimization Software Systems. EUROCAST 2007: 747-754 - [c1]Gabriel Kronberger, Roland Braune:
Bandit-Based Monte-Carlo Planning for the Single-Machine Total Weighted Tardiness Scheduling Problem. EUROCAST 2007: 837-844
Coauthor Index
[c70] [c63] [i26] [i15] [i12] [i9] [i8] [i7] [i6] [j8] [c54] [c52] [c51] [c48] [c47] [i5] [j6] [c45] [c44] [c43] [c42] [c41] [c39] [c38] [j4] [c36] [c35] [c34] [c32] [c31] [c30] [p5] [p4] [j3] [c28] [c27] [j1] [c24] [c23] [c21] [c20] [i3] [i2] [c18] [c16] [i1] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c6] [c5] [c4] [c3] [p1] [c2]
[j9] [c68] [c63] [i26] [i22] [i19] [i18] [i16] [i13] [i10] [i9] [i8] [i7] [i6] [j8] [c56] [c54] [c50] [c49] [c48] [c47] [i5] [j6] [c46] [c45] [c44] [c43] [c42] [c41] [c39] [c38] [c36] [c35] [c34] [c32] [c31] [c30] [p5] [p4] [p3] [j3] [c29] [c28] [c27] [j1] [c25] [c24] [c23] [c22] [c21] [c20] [i4] [i2] [c18] [c16] [i1] [c15] [c14] [c12] [c10] [c9] [c8]
Stefan Wagner 0002
aka: Stefan A. Wagner
aka: Stefan A. Wagner
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 21:17 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: