Matthias Jakobs

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 20

Top Topics

Ensemble Learning

Akaike Information Criterion

Model Selection

Top Venues

Publications

Matthias Jakobs, Amal Saadallah
Explainable Adaptive Tree-based Model Selection for Time Series Forecasting. CoRR (2024)
Raoul Heese, Thore Gerlach, Sascha Mücke, Sabine Müller, Matthias Jakobs, Nico Piatkowski
Explainable Quantum Machine Learning. CoRR (2023)
Sebastian Müller, Vanessa Toborek, Katharina Beckh, Matthias Jakobs, Christian Bauckhage, Pascal Welke
An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning. CoRR (2023)
Raoul Heese, Sascha Mücke, Matthias Jakobs, Thore Gerlach, Nico Piatkowski
Shapley Values with Uncertain Value Functions. CoRR (2023)
Raoul Heese, Sascha Mücke, Matthias Jakobs, Thore Gerlach, Nico Piatkowski
Shapley Values with Uncertain Value Functions. IDA (2023)
Raphael Fischer, Matthias Jakobs, Katharina Morik
Energy Efficiency Considerations for Popular AI Benchmarks. CoRR (2023)
Katharina Beckh, Sebastian Müller, Matthias Jakobs, Vanessa Toborek, Hanxiao Tan, Raphael Fischer, Pascal Welke, Sebastian Houben, Laura von Rüden
Harnessing Prior Knowledge for Explainable Machine Learning: An Overview. SaTML (2023)
Matthias Jakobs, Amal Saadallah
Explainable Adaptive Tree-based Model Selection for Time-Series Forecasting. ICDM (2023)
Amal Saadallah, Matthias Jakobs
Online Deep Hybrid Ensemble Learning for Time Series Forecasting. ECML/PKDD (5) (2023)
Sebastian Müller, Vanessa Toborek, Katharina Beckh, Matthias Jakobs, Christian Bauckhage, Pascal Welke
An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning. ECML/PKDD (3) (2023)
Katharina Morik, Helena Kotthaus, Raphael Fischer, Sascha Mücke, Matthias Jakobs, Nico Piatkowski, Andreas Pauly, Lukas Heppe, Danny Heinrich
Yes we care!-Certification for machine learning methods through the care label framework. Frontiers Artif. Intell. 5 (2022)
Raphael Fischer, Matthias Jakobs, Sascha Mücke, Katharina Morik
A Unified Framework for Assessing Energy Efficiency of Machine Learning. PKDD/ECML Workshops (1) (2022)
Amal Saadallah, Matthias Jakobs, Katharina Morik
Explainable online ensemble of deep neural network pruning for time series forecasting. Mach. Learn. 111 (9) (2022)
Matthias Jakobs, Helena Kotthaus, Ines Röder, Maximilian Baritz
SancScreen: Towards a Real-world Dataset for Evaluating Explainability Methods. LWDA (2022)
Katharina Morik, Helena Kotthaus, Lukas Heppe, Danny Heinrich, Raphael Fischer, Sascha Mücke, Andreas Pauly, Matthias Jakobs, Nico Piatkowski
Yes We Care! - Certification for Machine Learning Methods through the Care Label Framework. CoRR (2021)
Katharina Beckh, Sebastian Müller, Matthias Jakobs, Vanessa Toborek, Hanxiao Tan, Raphael Fischer, Pascal Welke, Sebastian Houben, Laura von Rüden
Explainable Machine Learning with Prior Knowledge: An Overview. CoRR (2021)
Amal Saadallah, Matthias Jakobs, Katharina Morik
Explainable Online Deep Neural Network Selection Using Adaptive Saliency Maps for Time Series Forecasting. ECML/PKDD (1) (2021)
Raphael Fischer, Matthias Jakobs, Sascha Mücke, Katharina Morik
Solving Abstract Reasoning Tasks with Grammatical Evolution. LWDA (2020)
Thomas Kirks, Jana Jost, Tim Uhlott, Julian Püth, Matthias Jakobs
Evaluation of the Application of Smart Glasses for Decentralized Control Systems in Logistics. ITSC (2019)
Thomas Kirks, Jana Jost, Tim Uhlott, Matthias Jakobs
Towards Complex Adaptive Control Systems for Human-Robot-Interaction in Intralogistics. ITSC (2018)