Bernd Bischl
Author of 33 CRAN packages
Bernd Bischl has worked on 33 packages, which is nothing short of amazing. Who needs sleep when you've got code to write? Bernd Bischl worked with over 69 collaborators. That's a huge group of developers—almost like a coding festival!
33 Packages
- BBmiscMiscellaneous Helper Functions for B. Bischl
- BatchExperimentsStatistical Experiments on Batch Computing Clusters
- BatchJobsBatch Computing with R
- OpenMLOpen Machine Learning and Open Data Platform
- ParamHelpersHelpers for Parameters in Black-Box Optimization, Tuning and Machine Learning
- RBPcurveThe Residual-Based Predictiveness Curve
- aslibInterface to the Algorithm Selection Benchmark Library
- batchtoolsTools for Computation on Batch Systems
- checkmateFast and Versatile Argument Checks
- farffA Faster 'ARFF' File Reader and Writer
- fmeffectsModel-Agnostic Interpretations with Forward Marginal Effects
- llamaLeveraging Learning to Automatically Manage Algorithms
- mcboostMulti-Calibration Boosting
- mcoMultiple Criteria Optimization Algorithms and Related Functions
- mlrMachine Learning in R
- mlr3benchmarkAnalysis and Visualisation of Benchmark Experiments
- mlr3fdaExtending 'mlr3' to Functional Data Analysis
- mlr3filtersFilter Based Feature Selection for 'mlr3'
- mlr3fselectFeature Selection for 'mlr3'
- mlr3hyperbandHyperband for 'mlr3'
- mlr3mboFlexible Bayesian Optimization
- mlr3pipelinesPreprocessing Operators and Pipelines for 'mlr3'
- mlr3resamplingResampling Algorithms for 'mlr3' Framework
- mlr3summaryModel and Learner Summaries for 'mlr3'
- mlr3torchDeep Learning with 'mlr3'
- mlrCPOComposable Preprocessing Operators and Pipelines for Machine Learning
- mlrMBOBayesian Optimization and Model-Based Optimization of Expensive Black-Box Functions
- paradoxDefine and Work with Parameter Spaces for Complex Algorithms
- parallelMapUnified Interface to Parallelization Back-Ends
- tspmetaInstance Feature Calculation and Evolutionary Instance Generation for the Traveling Salesman Problem
- bbotkBlack-Box Optimization Toolkit
- mlr3Machine Learning in R - Next Generation
- mlr3tuningHyperparameter Optimization for 'mlr3'
Team
- Michel Lang
- Dirk Surmann
- Jakob Richter
- Jakob Bossek
- Daniel Horn
- Olaf Mersmann
- Henrik Bengtsson
- Giuseppe Casalicchio
- Pascal Kerschke
- Benjamin Hofner
- Dominik Kirchhoff
- Joaquin Vanschoren
- Karin Schork
- Lars Kotthoff
- Damir Pulatov
- Dénes Tóth
- Marc Becker
- Holger Löwe
- Christian Scholbeck
- Christian Heumann
- Barry Hurley
- Talal Rahwan
- Susanne Dandl
- Sebastian Fischer
- Florian Pfisterer
- Christoph Kern
- Carolin Becker
- Detlef Steuer
- Heike Trautmann
- Kalyanmoy Deb
- Philipp Probst
- Patrick Schratz
- Martin Binder
- Janek Thomas
- Christoph Molnar
- Julia Schiffner
- Zachary Jones
- Mason Gallo
- Erich Studerus
- Leonard Judt
- Tobias Kuehn
- Florian Fendt
- Xudong Sun
- Bruno Vieira
- Laura Beggel
- Quay Au
- Stefan Coors
- Steve Bronder
- Alexander Engelhardt
- Annette Spooner
- Sonabend Raphael
- Fabian Scheipl
- Maximilian Mücke
- John Zobolas
- Sebastian Gruber
- Julia Moosbauer
- Lennart Schneider
- Carlos Fonseca
- Michael H. Buselli
- Wessel Dankers
- Manuel Lopez-Ibanez
- Luis Paquete
- Lona Koers
- Keno Mersmann
- Raphael Sonabend
- Toby Hocking
- Ludwig Bothmann
- Lukas Burk
- Daniel Schalk