Jakob Gawlikowski

According to our database, Jakob Gawlikowski authored at least 21 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Data-Centric Benchmark for Label Noise Estimation and Ranking in Remote Sensing Image Segmentation.

Keiller Nogueira, Codrut-Andrei Diaconu, Dávid Kerekes, Jakob Gawlikowski, Cédric Léonard, Nassim Ait Ali Braham, June Moh Goo, Zichao Zeng, Zhipeng Liu, Pallavi Jain, Andrea Nascetti, Ronny Hänsch

CoRR, March, 2026

2025

Lightning UQ Box: Uncertainty Quantification for Neural Networks.

Nils Lehmann, Nina Maria Gottschling, Jakob Gawlikowski, Adam J. Stewart, Stefan Depeweg, Eric T. Nalisnick

J. Mach. Learn. Res., 2025

2024

Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning.

Nils Lehmann, Jakob Gawlikowski, Adam J. Stewart, Vytautas Jancauskas, Stefan Depeweg, Eric T. Nalisnick, Nina Maria Gottschling

CoRR, 2024

Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-Regenerative Life Support System Telemetry.

Ferdinand Rewicki, Jakob Gawlikowski, Julia Niebling, Joachim Denzler

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2024

Exploiting Text-Image Latent Spaces for the Description of Visual Concepts.

Laines Schmalwasser, Jakob Gawlikowski, Joachim Denzler, Julia Niebling

Proceedings of the Pattern Recognition - 27th International Conference, 2024

Efficient Data Source Relevance Quantification for Multi-Source Neural Networks.

Jakob Gawlikowski, Nina Maria Gottschling

Proceedings of the 35th British Machine Vision Conference, 2024

2023

Handling unexpected inputs: incorporating source-wise out-of-distribution detection into SAR-optical data fusion for scene classification.

Jakob Gawlikowski, Sudipan Saha, Julia Niebling, Xiao Xiang Zhu

EURASIP J. Adv. Signal Process., December, 2023

A survey of uncertainty in deep neural networks.

Jakob Gawlikowski, Cedrique Rovile Njieutcheu Tassi, Mohsin Ali, Jongseok Lee, Matthias Humt, Jianxiang Feng, Anna M. Kruspe, Rudolph Triebel, Peter Jung, Ribana Roscher, Muhammad Shahzad, Wen Yang, Richard Bamler, Xiaoxiang Zhu

Artif. Intell. Rev., October, 2023

The Unreasonable Effectiveness of Deep Evidential Regression.

Nis Meinert, Jakob Gawlikowski, Alexander Lavin

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Leveraging Graph and Deep Learning Uncertainties to Detect Anomalous Maritime Trajectories.

Sandeep Kumar Singh, Jaya Shradha Fowdur, Jakob Gawlikowski, Daniel Medina

IEEE Trans. Intell. Transp. Syst., 2022

An Advanced Dirichlet Prior Network for Out-of-Distribution Detection in Remote Sensing.

Jakob Gawlikowski, Sudipan Saha, Anna M. Kruspe, Xiao Xiang Zhu

IEEE Trans. Geosci. Remote. Sens., 2022

Explaining the Effects of Clouds on Remote Sensing Scene Classification.

Jakob Gawlikowski, Patrick Ebel, Michael Schmitt, Xiao Xiang Zhu

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022

Structuring Uncertainty for Fine-Grained Sampling in Stochastic Segmentation Networks.

Frank Nussbaum, Jakob Gawlikowski, Julia Niebling

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The impact of averaging logits over probabilities on ensembles of neural networks.

Cedrique Rovile Njieutcheu Tassi, Jakob Gawlikowski, Auliya Unnisa Fitri, Rudolph Triebel

Proceedings of the Workshop on Artificial Intelligence Safety 2022 (AISafety 2022) co-located with the Thirty-First International Joint Conference on Artificial Intelligence and the Twenty-Fifth European Conference on Artificial Intelligence (IJCAI-ECAI-2022), 2022

Compact Feature Representation for Unsupervised Ood Detection.

Sudipan Saha, Jakob Gawlikowski, Jay Nandy, Xiao Xiang Zhu

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

Estimating Uncertainty of Deep Learning Multi-Label Classifications Using Laplace Approximation.

Ferdinand Rewicki, Jakob Gawlikowski

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

Robust Distribution-Shift Aware Sar-Optical data Fusion for Multi-Label Scene Classification.

Jakob Gawlikowski, Sudipan Saha, Julia Niebling, Xiao Xiang Zhu

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

2021

Leveraging Evidential Deep Learning Uncertainties with Graph-based Clustering to Detect Anomalies.

Sandeep Kumar Singh, Jaya Shradha Fowdur, Jakob Gawlikowski, Daniel Medina

CoRR, 2021

Out-of-distribution detection in satellite image classification.

Jakob Gawlikowski, Sudipan Saha, Anna M. Kruspe, Xiao Xiang Zhu

CoRR, 2021

Towards Out-of-Distribution Detection for Remote Sensing.

Jakob Gawlikowski, Sudipan Saha, Anna M. Kruspe, Xiao Xiang Zhu

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2020

On the Fusion Strategies of Sentinel-1 and Sentinel-2 Data for Local Climate Zone Classification.

Jakob Gawlikowski, Michael Schmitt, Anna M. Kruspe, Xiaoxiang Zhu

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020