Joachim Sicking

18 papers C 1Journal 14Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	FOCUS: Internal MLLM Representations for Efficient Fine-Grained Visual Question Answering. CoRR Liangyu Zhong, Fabio Rosenthal, Joachim Sicking, Fabian Hüger, Thorsten Bagdonat, Hanno Gottschalk, Leo Schwinn
2024	J	`jnl`	VL4AD: Vision-Language Models Improve Pixel-wise Anomaly Detection. CoRR Liangyu Zhong, Joachim Sicking, Fabian Hüger, Hanno Gottschalk
2024	J	`jnl`	Wasserstein dropout. Mach. Learn. Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Stefan Wrobel, Asja Fischer
2023	J	`jnl`	Guideline for Trustworthy Artificial Intelligence - AI Assessment Catalog. CoRR Maximilian Poretschkin, Anna Schmitz, Maram Akila, Linara Adilova, Daniel Becker, Armin B. Cremers, Dirk Hecker, Sebastian Houben, Michael Mock, Julia Rosenzweig, Joachim Sicking, Elena Schulz, Angelika Voss, Stefan Wrobel
2023	—	`—`	On Modeling and Assessing Uncertainty Estimates in Neural Learning Systems Joachim Sicking
2022	J	`jnl`	A Survey on Uncertainty Toolkits for Deep Learning. CoRR Maximilian Pintz, Joachim Sicking, Maximilian Poretschkin, Maram Akila
2022	C	`conf`	DenseHMM: Learning Hidden Markov Models by Learning Dense Representations. ICPRAM Joachim Sicking, Maximilian Pintz, Maram Akila, Tim Wirtz
2022	J	`jnl`	Tailored Uncertainty Estimation for Deep Learning Systems. CoRR Joachim Sicking, Maram Akila, Jan David Schneider, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel
2021	J	`jnl`	A Novel Regression Loss for Non-Parametric Uncertainty Optimization. CoRR Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel
2021	J	`jnl`	Approaching Neural Network Uncertainty Realism. CoRR Joachim Sicking, Alexander Kister, Matthias Fahrland, Stefan Eickeler, Fabian Hüger, Stefan Rüping, Peter Schlicht, Tim Wirtz
2021	J	`jnl`	Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety. CoRR Sebastian Houben, Stephanie Abrecht, Maram Akila, Andreas Bär, Felix Brockherde, Patrick Feifel, Tim Fingscheidt, Sujan Sai Gannamaneni, Seyed Eghbal Ghobadi, Ahmed Hammam, Anselm Haselhoff, Felix Hauser, Christian Heinzemann, Marco Hoffmann, Nikhil Kapoor, Falk Kappel, Marvin Klingner, Jan Kronenberger, Fabian Küppers, Jonas Löhdefink, Michael Mlynarski, Michael Mock, Firas Mualla, Svetlana Pavlitskaya, Maximilian Poretschkin, Alexander Pohl, Varun Ravi Kumar, Julia Rosenzweig, Matthias Rottmann, Stefan Rüping, Timo Sämann, Jan David Schneider, Elena Schulz, Gesina Schwalbe, Joachim Sicking, Toshika Srivastava, Serin Varghese, Michael Weber, Sebastian Wirkert, Tim Wirtz, Matthias Woehrle
2021	—	`conf`	Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities. CVPR Workshops Julia Rosenzweig, Joachim Sicking, Sebastian Houben, Michael Mock, Maram Akila
2021	J	`jnl`	Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities. CoRR Julia Rosenzweig, Joachim Sicking, Sebastian Houben, Michael Mock, Maram Akila
2020	J	`jnl`	Characteristics of Monte Carlo Dropout in Wide Neural Networks. CoRR Joachim Sicking, Maram Akila, Tim Wirtz, Sebastian Houben, Asja Fischer
2020	J	`jnl`	DenseHMM: Learning Hidden Markov Models by Learning Dense Representations. CoRR Joachim Sicking, Maximilian Pintz, Maram Akila, Tim Wirtz
2020	J	`jnl`	Second-Moment Loss: A Novel Regression Objective for Improved Uncertainties. CoRR Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel
2018	—	`conf`	Efficient Decentralized Deep Learning by Dynamic Model Averaging. ECML/PKDD (1) Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel
2018	J	`jnl`	Efficient Decentralized Deep Learning by Dynamic Model Averaging. CoRR Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel