Sascha Saralajew

43 papers A* 3A 1B 8C 4Journal 17Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Prototype-Based Learning for Healthcare: A Demonstration of Interpretable AI. CoRR Ashish Rana, Ammar Shaker, Sascha Saralajew, Takashi Suzuki, Kosuke Yasuda, Shintaro Kato, Toshikazu Wada, Toshiyuki Fujikawa, Toru Kikutsuji
2025	A*	`conf`	A Robust Prototype-Based Network with Interpretable RBF Classifier Foundations. AAAI Sascha Saralajew, Ashish Rana, Thomas Villmann, Ammar Shaker
2025	—	`conf`	Prototype-Based Learning for Healthcare: A Demonstration of Interpretable AI. ICDM (Workshops) Ashish Rana, Ammar Shaker, Sascha Saralajew, Takashi Suzuki, Kosuke Yasuda, Shintaro Kato, Toshikazu Wada, Toshiyuki Fujikawa, Toru Kikutsuji
2024	—	`conf`	A Human-Centric Assessment of the Usefulness of Attribution Methods in Computer Vision. ECML/PKDD (5) Wiem Ben Rim, Ammar Shaker, Zhao Xu, Kiril Gashteovski, Bhushan Kotnis, Carolin Lawrence, Jürgen Quittek, Sascha Saralajew
2024	J	`jnl`	A Robust Prototype-Based Network with Interpretable RBF Classifier Foundations. CoRR Sascha Saralajew, Ashish Rana, Thomas Villmann, Ammar Shaker
2024	J	`jnl`	Aligning Generalisation Between Humans and Machines. CoRR Filip Ilievski, Barbara Hammer, Frank van Harmelen, Benjamin Paassen, Sascha Saralajew, Ute Schmid, Michael Biehl, Marianna Bolognesi, Xin Luna Dong, Kiril Gashteovski, Pascal Hitzler, Giuseppe Marra, Pasquale Minervini, Martin Mundt, Axel-Cyrille Ngonga Ngomo, Alessandro Oltramari, Gabriella Pasi, Zeynep G. Saribatur, Luciano Serafini, John Shawe-Taylor, Vered Shwartz, Gabriella Skitalinskaya, Clemens Stachl, Gido M. van de Ven, Thomas Villmann
2024	—	`conf`	Biologically-Informed Shallow Classification Learning Integrating Pathway Knowledge. BIOSTEC (1) Julius Voigt, Sascha Saralajew, Marika Kaden, Katrin Sophie Bohnsack, Lynn V. Reuss, Thomas Villmann
2024	C	`conf`	Combining Visual Saliency Methods and Sparse Keypoint Annotations to Create Object Representations for Providently Detecting Vehicles at Night. IV Lukas Ewecker, Lars Ohnemus, Robin Schwager, Stefan Roos, Tim Brühl, Sascha Saralajew
2024	C	`conf`	Detecting Oncoming Vehicles at Night in Urban Scenarios - An Annotation Proof-Of-Concept. IV Lukas Ewecker, Niklas Wagner, Tim Brühl, Robin Schwager, Tin Stribor Sohn, Alexander Engelsberger, Jensun Ravichandran, Hanno Stage, Jacob Langner, Sascha Saralajew
2024	B	`conf`	Domain Knowledge Integration in Machine Learning Systems - An Introduction. ESANN Marika Kaden, Sascha Saralajew, Thomas Villmann
2024	J	`jnl`	Generalization by People and Machines (Dagstuhl Seminar 24192). Dagstuhl Reports Barbara Hammer, Filip Ilievski, Sascha Saralajew, Frank van Harmelen
2024	—	`conf`	Robust Text Classification: Analyzing Prototype-Based Networks. EMNLP (Findings) Zhivar Sourati, Darshan Deshpande, Filip Ilievski, Kiril Gashteovski, Sascha Saralajew
2023	J	`jnl`	Provident vehicle detection at night for advanced driver assistance systems. Auton. Robots Lukas Ewecker, Ebubekir Asan, Lars Ohnemus, Sascha Saralajew
2023	J	`jnl`	Robust Text Classification: Analyzing Prototype-Based Networks. CoRR Zhivar Sourati, Darshan Deshpande, Filip Ilievski, Kiril Gashteovski, Sascha Saralajew
2023	J	`jnl`	The coming of age of interpretable and explainable machine learning models. Neurocomputing Paulo J. G. Lisboa, Sascha Saralajew, Alfredo Vellido, Ricardo Fernández-Domenech, Thomas Villmann
2022	J	`jnl`	A Human-Centric Assessment Framework for AI. CoRR Sascha Saralajew, Ammar Shaker, Zhao Xu, Kiril Gashteovski, Bhushan Kotnis, Wiem Ben Rim, Jürgen Quittek, Carolin Lawrence
2022	B	`conf`	A Learning Vector Quantization Architecture for Transfer Learning Based Classification in Case of Multiple Sources by Means of Null-Space Evaluation. IDA Thomas Villmann, Daniel Staps, Jensun Ravichandran, Sascha Saralajew, Michael Biehl, Marika Kaden
2022	J	`jnl`	Combining Visual Saliency Methods and Sparse Keypoint Annotations to Providently Detect Vehicles at Night. CoRR Lukas Ewecker, Lars Ohnemus, Robin Schwager, Stefan Roos, Sascha Saralajew
2021	A	`conf`	A Dataset for Provident Vehicle Detection at Night. IROS Sascha Saralajew, Lars Ohnemus, Lukas Ewecker, Ebubekir Asan, Simon T. Isele, Stefan Roos
2021	J	`jnl`	A Dataset for Provident Vehicle Detection at Night. CoRR Sascha Saralajew, Lars Ohnemus, Lukas Ewecker, Ebubekir Asan, Simon T. Isele, Stefan Roos
2021	B	`conf`	Domain Adversarial Tangent Learning Towards Interpretable Domain Adaptation. ESANN Christoph Raab, Sascha Saralajew, Frank-Michael Schleif
2021	J	`jnl`	Provident Vehicle Detection at Night for Advanced Driver Assistance Systems. CoRR Lukas Ewecker, Ebubekir Asan, Lars Ohnemus, Sascha Saralajew
2021	C	`conf`	Radar Artifact Labeling Framework (RALF): Method for Plausible Radar Detections in Datasets. VEHITS Simon T. Isele, Marcel P. Schilling, Fabian E. Klein, Sascha Saralajew, J. Marius Zoellner
2021	B	`conf`	The Coming of Age of Interpretable and Explainable Machine Learning Models. ESANN Paulo Lisboa, Sascha Saralajew, Alfredo Vellido, Thomas Villmann
2021	J	`jnl`	The Resolved Mutual Information Function as a Structural Fingerprint of Biomolecular Sequences for Interpretable Machine Learning Classifiers. Entropy Katrin Sophie Bohnsack, Marika Kaden, Julia Abel, Sascha Saralajew, Thomas Villmann
2020	A*	`conf`	Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms. NeurIPS Sascha Saralajew, Lars Holdijk, Thomas Villmann
2020	—	`—`	New Prototype Concepts in Classification Learning. Sascha Saralajew
2020	C	`conf`	Provident Detection of Vehicles at Night. IV Emilio Oldenziel, Lars Ohnemus, Sascha Saralajew
2020	J	`jnl`	Provident Vehicle Detection at Night: The PVDN Dataset. CoRR Lars Ohnemus, Lukas Ewecker, Ebubekir Asan, Stefan Roos, Simon T. Isele, Jakob Ketterer, Leopold Müller, Sascha Saralajew
2020	J	`jnl`	Radar Artifact Labeling Framework (RALF): Method for Plausible Radar Detections in Datasets. CoRR Simon T. Isele, Marcel P. Schilling, Fabian E. Klein, Sascha Saralajew, J. Marius Zoellner
2020	J	`jnl`	Variants of DropConnect in Learning vector quantization networks for evaluation of classification stability. Neurocomputing Jensun Ravichandran, Marika Kaden, Sascha Saralajew, Thomas Villmann
2019	A*	`conf`	Classification-by-Components: Probabilistic Modeling of Reasoning over a Set of Components. NeurIPS Sascha Saralajew, Lars Holdijk, Maike Rees, Ebubekir Asan, Thomas Villmann
2019	B	`conf`	DropConnect for Evaluation of Classification Stability in Learning Vector Quantization. ESANN Jensun Ravichandran, Sascha Saralajew, Thomas Villmann
2019	—	`conf`	Robustness of Generalized Learning Vector Quantization Models Against Adversarial Attacks. WSOM+ Sascha Saralajew, Lars Holdijk, Maike Rees, Thomas Villmann
2019	J	`jnl`	Robustness of Generalized Learning Vector Quantization Models against Adversarial Attacks. CoRR Sascha Saralajew, Lars Holdijk, Maike Rees, Thomas Villmann
2018	—	`conf`	Probabilistic Learning Vector Quantization with Cross-Entropy for Probabilistic Class Assignments in Classification Learning. ICAISC (1) Andrea Villmann, Marika Kaden, Sascha Saralajew, Thomas Villmann
2018	J	`jnl`	Prototype-based Neural Network Layers: Incorporating Vector Quantization. CoRR Sascha Saralajew, Lars Holdijk, Maike Rees, Thomas Villmann
2018	B	`conf`	Reliable Patient Classification in Case of Uncertain Class Labels Using a Cross-Entropy Approach. ESANN Andrea Villmann, Marika Kaden, Sascha Saralajew, Wieland Hermann, Thomas Villmann
2017	—	`conf`	Fusion of deep learning architectures, multilayer feedforward networks and learning vector quantizers for deep classification learning. WSOM Thomas Villmann, Michael Biehl, Andrea Villmann, Sascha Saralajew
2017	B	`conf`	Transfer learning in classification based on manifolc. models and its relation to tangent metric learning. IJCNN Sascha Saralajew, Thomas Villmann
2016	—	`conf`	Adaptive Hausdorff Distances and Tangent Distance Adaptation for Transformation Invariant Classification Learning. ICONIP (3) Sascha Saralajew, David Nebel, Thomas Villmann
2016	B	`conf`	Adaptive tangent distances in generalized learning vector quantization for transformation and distortion invariant classification learning. IJCNN Sascha Saralajew, Thomas Villmann
2016	—	`conf`	Self-Adjusting Reject Options in Prototype Based Classification. WSOM Thomas Villmann, Marika Kaden, Andrea Bohnsack, J.-M. Villmann, T. Drogies, Sascha Saralajew, Barbara Hammer