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seminar_multimodal_dl
https://slds-lmu.github.io/seminar_multimodal_dl/lecture_i2ml
I2ML lecture repositoryyahpo_gym
Surrogate benchmarks for HPO problemsimlplots
Create Interpretable Machine Learning plots with an interactive Shiny based dashboardlecture_dl4nlp
Repo containing all the lecture material for the dl4nlp coursepaper_2019_iml_measures
Quantifying Interpretability of Arbitrary Machine Learning Models Through Functional Decompositionlecture_iml
code_pitfalls_iml
This repository contains the code for all figures in the paper "General Pitfalls of Model-agnostic Interpretation Methods for Machine Learning Models"i2ml
https://slds-lmu.github.io/i2ml/seminar_nlp_ss20
Link to websitelecture_optimization
tsclassification
Wrapping the Time-Series Classification Java Implementations for Rmosmafs
Multi-Objective Simultaneous Model and Feature Selectionlatex-math
qdo_yahpo
A Collection of Quality Diversity Optimization Problems Derived from Hyperparameter Optimization of Machine Learning Modelslecture_i2ml_learnr_tutorials
lrz_configs
yahpo_data
Data required for slds-lmu/yahpo_gympaper_2021_categorical_feature_encodings
hpo_ela
paper_2023_survival_benchmark
Benchmark for Burk et al. (2024)iml-shiny-summary
Shiny Dashboard showing an interpretation summary for any modeli2dl
https://slds-lmu.github.io/i2dl/wildlife-ml
paper_2021_xautoml
lecture_sl
vistool
wildlife-experiments
seminar_website_skeleton
jTSC4R
Java Time Series Classification code to use in Rpaper_2021_multi_fidelity_surrogates
Surrogate benchmarks for HPO problemssurrogates
grouped_feat_imp_and_effects
dl4nlp
https://slds-lmu.github.io/dl4nlp/rcourses_notebook_deeplearning
scetchpaper_2019_multiobjective_rfms
High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributionslecture_advml
yahpo_exps
Experiments for yahpo gymlecture_template
rcourses_notebook_clustering
paper_2019_variationalResampleDistributionShift
Variational Resampling Based Assessment of Deep Neural Networks Robustness under Distribution Shiftmlw-htr
ame
average marginal effects for machine learningqdo_nas
paper_2024_rpid
benchmark_2022_counterfactuals
Benchmark code for paper on counterfactuals R Packagephd_thesis_dummy_template
rcourses_notebook_ml
mbt_comparison
mobafeas
Model Based Feature Selectionintroduction_iml_bliz_summerschool
This repository provides a short introduction into the most popular model-agnostic IML (interpretable machine learning) methods. A presentation containing the theoretical background and examples as well as excercises on real-world data are included.lecture_i2dl
Introduction to Deep Leaninglecture_service
Service repo for common infrastructure across all open source lecturespaper_2023_eagga
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Modelspaper_2023_regression_suite
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