Publications

For additional information and material about our publications,
visit https://bib.sebastianstober.de

2024

  • Neuroscience-Inspired Analysis and Visualization of Deep Neural Networks
    Valerie Krug.
    Dissertation/PhD thesis, Otto-von-Guericke-Universität Magdeburg, Fakultät für Informatik
    [URL]

2023

  • Visualizing Bias in Activations of Deep Neural Networks as Topographic Maps
    Valerie Krug, Christopher Olson and Sebastian Stober. 
    In: Proceedings of the 1st Workshop on Fairness and Bias in AI (AEQUITAS 2023), co-located with 26th European Conference on Artificial Intelligence (ECAI 2023) Kraków, Poland. CEUR-WS, 2023
    [URL]

  • Emo-StarGAN: A Semi-Supervised Any-to-Many Non-Parallel Emotion-Preserving Voice Conversion
    Suhita Ghosh*, Arnab Das*, Yamini Sinha, Ingo Siegert, Tim Polzehl and Sebastian Stober 
    In: Interspeech 2023 - Dublin, Ireland, 20-24 August 2023
    [URL[Github]

  • StarGAN-VC++: Towards Emotion Preserving Voice Conversion Using Deep Embeddings.
    Arnab Das*, Suhita Ghosh*, Tim Polzehl and Sebastian Stober
    In: 12th Speech Synthesis Workshop (SSW) 2023 - Grenoble, France, 26-30 August 2023
    [URL] [Github]

  • Anonymization of Stuttered Speech – Removing Speaker Information while Preserving the Utterance.
    Jan Hintz*, Sebastian Bayerl*, Yamini Sinha, Suhita Ghosh, Martha Schubert, Sebastian Stober, Korbinian Riedhammer and Ingo Siegert

    In: 3rd Symposium on Security and Privacy in Speech Communication - Dublin, Ireland, 19 August 2023
    [URL]

  • Visualizing Deep Neural Networks with Topographic Activation Maps.
    Valerie Krug, Raihan Kabir Ratul, Christopher Olson and Sebastian Stober.
    In: HHAI 2023: Augmenting Human Intellect. IOS Press, 2023. 138-152.
    [URL] [Github]

  • AI Course Design Planning Framework: Developing Domain-Specific AI Education Courses.
    Johannes Schleiss, Matthias Carl Laupichler, Tobias Raupach, Sebastian Stober
    Educ. Sci. 2023, 13(9), 954; [https://doi.org/10.3390/educsci13090954]

  • Better ready than just aware: Data and AI Literacy as an enabler for informed decision making in the data age.
    Katharina Schüller, Florian Rampelt, Henning Koch, Johannes Schleiss.
    In: INFORMATIK 2023. []

  • Planning Interdisciplinary Artificial Intelligence Courses.
    Johannes Schleiss, Sebastian Stober.
    In: Proceedings of Society for Engineering Education (SEFI) Annual Conference 2023. [https://doi.org/10.21427/V4ZV-HR52]


  • Curriculum Workshop as Method of Interdisciplinary Curriculum Development: A Case Study of Artificial Intelligence in Engineering.
    Johannes Schleiss, Anke Manukjan, Michelle Ines Bieber, Philipp Pohlenz, Sebastian Stober.
    In: Proceedings of Society for Engineering Education (SEFI) Annual Conference 2023. [https://doi.org/10.21427/XTAE-AS48]


  • Trustworthy Academic Risk Prediction with Explainable Boosting Machines.
    Vegenshanti Dsilva, Johannes Schleiss and Sebastian Stober.
    In: Proceedings of the International Conference on Artificial Intelligence in Education, 2023.
    [https://doi.org/10.1007/978-3-031-36272-9_38]

  • Improving Voice Conversion for Dissimilar Speakers Using Perceptual Losses.
    Suhita Ghosh, Yamini Sinha, Ingo Siegert and Sebastian Stober.
    In: DAGA 2023 - Hamburg: Deutsche Gesellschaft für Akustik e.V. (DEGA). - 2023, S. 1358-1361.
    [URL]

2022

  • Voice Privacy Leveraging Multi-Scale Blocks with ECAPA-TDNN SE-Res2NeXT Extension for Speaker Anonymization.
    Razieh Khamsehashari, Yamini Sinha, Jan Hintz, Suhita Ghosh, Tim Polzehl, Carlos Franzreb, Sebastian Stober and Ingo Siegert.
    In: 2nd Symposium on Security and Privacy in Speech Communication - Incheon, Korea, 23-24 September 2022 - International Speech Communication Association. https://doi.org/10.21437/spsc.2022-8

  • Projektseminar „Künstliche Intelligenz in den Neurowissenschaften – interdisziplinäre und anwendungsnahe Lehre umsetzen“.
    Johannes Schleiss, Robert Brockhoff und Sebastian Stober.

    In: Mah, D.-K., & Torner, C. (Hrsg.) (2022): Anwendungsorientierte Hochschullehre zu Künstlicher Intelligenz. Impulse aus dem Fellowship-Programm zur Integration von KI-Campus-Lernangeboten. Berlin: KI-Campus. https://doi.org/10.5281/zenodo.7319832

  • Rahmenbedingungen für Künstliche Intelligenz in Educational Technology.
    Johannes Schleiss und Stefan Göllner.
    IN: Proceedings of DELFI Workshops 2022 - Die 20. Fachtagung Bildungstechnologien, 2022.
    [URL]

  • An Interdisciplinary Competence Profile for AI in Engineering.
    Johannes Schleiss; Michelle Ines Bieber; Anke Manukjan; Lars Kellner & Sebastian Stober.
    In: Proceedings of the 50th European Society for Engineering Education (SEFI) Anual Conference, 2022.
    [URL]

  • Teaching AI Competencies in Engineering using Projects and Open Educational Resources.
    Johannes Schleiss; Julia Hense; Andreas Kist; Jörn Schlingensiepen & Sebastian Stober
    In: Proceedings of the 50th European Society for Engineering Education (SEFI) Anual Conference, 2022.
    [URL]

  • Towards Patient Specific Reconstruction Using Perception-Aware CNN and Planning CT as Prior.
    Suhita Ghosh; Philipp Ernst; Georg Rose; Andreas Nürnberger and Sebastian Stober.

    In: IEEE 19th International Symposium on Biomedical Imaging (ISBI). IEEE, 2022.
    [URL]

  • Dual Branch Prior-SegNet: CNN for Interventional CBCT using Planning Scan and Auxiliary Segmentation Loss.
    Philipp Ernst, Suhita Ghosh, Georg Rose, Andreas Nürnberger
    .
    Medical Imaging with Deep Learning, MIDL 2022, Zürich, Switzerland, July 06, 2022, Medical Imaging with Deep Learning
    [URL]

  • Protecting Student Data in ML Pipelines: An Overview of Privacy-Preserving ML.
    Johannes Schleiss; Kolja Günther & Sebastian Stober.
    In: Proceedings of the International Conference on Artificial Intelligence in Education, 532-536, 2022.
    [URL]


  • BiTe-REx: An Explainable Bilingual Text Retrieval System in the Automotive Domain.
    Viju Sudhi; Sabine Wehnert; Norbert Michael Homner; Sebastian Ernst; Mark Gonter; Andreas Krug & Ernesto William De Luca.
    In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Pages 3251–3255, 2022.
    [URL]


  • Visualizing Deep Neural Networks with Topographic Activation Maps.
    Andreas Krug; Raihan Kabir Ratul & Sebastian Stober.
    In: arXiv preprint arXiv:2204.03528, 2022.
    [PDF] [github]

2021

  • Hierarchical Predictive Coding and Interpretable Audio Analysis-Synthesis.
    André Ofner; Johannes Schleiss & Sebastian Stober.

    In: Proc. of the 15th International Symposium on CMMR, 2021.
    [PDF]

  • Uncertainty-aware temporal self-learning (UATS) - semi-supervised learning for segmentation of prostate zones and beyond.
    Anneke Meyer; Suhita Ghosh; Daniel Schindele; Martin Schostak; Sebastian Stober; Christian Hansen & Marko Rak.
    In: Artificial intelligence in medicine: AIM - Amsterdam [u.a.]: Elsevier Science - AIM, Bd. 116, 2021.
    [PDF]

  • Analyzing and Visualizing Deep Neural Networks for Speech Recognition with Saliency-Adjusted Neuron Activation Profiles.
    Andreas Krug; Maral Ebrahimzadeh; Jost Alemann; Jens Johannsmeier & Sebastian Stober.
    In: Electronics 10 (11), 1350, 2021.
    [URL]

  • Perceptual Losses Facilitate CT Denoising and Artifact Removal.
    Suhita Ghosh; Andreas Krug; Georg Rose & Sebastian Stober.
    In: 2021 IEEE 2nd International Conference on Human-Machine Systems (ICHMS). IEEE, 2021.
    [URL]

  • Distributed Planning with Active Inference.
    André Ofner; Johannes Schleiss & Sebastian Stober.
    In: Bernstein Conference, 2021.
    [URL]

  • Visualizing Artificial Neural Network Activations as Topographic Maps.
    Andreas Krug; Raihan Kabir Ratul & Sebastian Stober.
    In: Bernstein Conference, 2021.
    [URL]

  • Few-Shot Bioacoustic Event Detection via Segmentation using Prototypical Networks.
    Jens Johannsmeier & Sebastian Stober.
    In: Detection and Classification of Acoustic Scenes and Events (DCASE), 2021.
    [PDF]

  • Approaching Scheduling Problems via a Deep Hybrid Greedy Model and Supervised Learning.
    Johann Schmidt & Sebastian Stober.
    In: IFAC-PapersOnline 54 (1), 805-810, 2021.
    [URL]

2020

  • Automatic prostate and prostate zones segmentation of magnetic resonance images using DenseNet-like U-net.
    Nader Aldoj; Federico Biavati; Florian Michallek; Sebastian Stober & Marc Dewey.
    In: Scientific Reports, Volume 10, Number 1, Springer Science and Business Media LLC, 2020.
    [DOI] [PDF]

  • Balancing Active Inference and Active Learning with Deep Variational Predictive Coding for EEG.
    André Ofner & Sebastian Stober.
    In: IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020), 2020.
    [URL]

  • Modeling perception with hierarchical prediction: Auditory segmentation with deep predictive coding locates candidate evoked potentials in EEG.
    André Ofner & Sebastian Stober.
    In: ResearchGATE: scientific neetwork ; the leading professional network for scientists - Cambridge, Mass.: ResearchGATE Corp., 2010, 2020.
    [URL] [PDF]

  • Applying deep learning to single-trial EEG data provides evidence for complementary theories on action control.
    Amirali Vahid; Moritz Mückschel; Sebastian Stober: Ann-Kathrin Stock & Christian Beste.
    In: Communications biology - London: Springer Nature, Vol. 3.2020, Art.-Nr. 112, 11, 2020.
    [DOI] [PDF]

  • Analyzing regions of safety for handling shared data in cooperative systems.
    Georg Jäger; Johannes Schleiss; Sasiporn Usanavasin; Sebastian Stober & Sebastian Zug.
    In: 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2020.
    [URL]

  • PredNet and Predictive Coding: A Critical Review.
    Roshan Prakash Rane; Edit Szügyi; Vageesh Saxena; André Ofner & Sebastian Stober.
    In: Proceedings of the 2020 International Conference on Multimedia Retrieval, ICMR ’20, Pages 233–241, Association for Computing Machinery, New York, NY, USA, 2020.
    [DOI] [PDF]

  • Exploration of interpretability techniques for deep COVID-19 classification using chest X-ray images.
    Soumick Chatterjee; Fatima Saad; Chompunuch Sarasaen; Suhita Ghosh; Rupali Khatun; Petia Radeva; Georg Rose; Sebastian Stober; Oliver Speck & Andreas Nürnberger.
    In: arXiv preprint arXiv:2006.02570, 2020.
    [PDF]

  • Gradient-adjusted neuron activation profiles for comprehensive introspection of convolutional speech recognition models.
    Andreas Krug & Sebastian Stober.
    In: arXiv preprint arXiv:2002.08125, 2020.
    [PDF]

2019

  • Window-Based Neural Tagging for Shallow Discourse Argument Labeling.
    René Knaebel; Manfred Stede & Sebastian Stober.
    In: Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), Pages 768-777, 2019.
    [DOI] [PDF]

  • The ISMIR Explorer – A Visual Interface for Exploring 20 Years of ISMIR Publications.
    Thomas Low; Christian Hentschel; Sayantan Polley; Anustup Das; Harald Sack; Andreas Nürnberger & Sebastian Stober.
    In: 20th International Society for Music Information Retrieval Conference (ISMIR’19), Pages 392-399, 2019.
    [PDF]

  • Predictive Coding Based Vision For Autonomous Cars.
    Roshan Prakash Rane;​ André Ofner; Shreyas Gite​ & Sebastian Stober.
    In: Computational Cognition 2019 Workshop, 2019.
    [URL]

  • Knowledge transfer in coupled predictive coding networks.
    André Ofner & Sebastian Stober.
    In: Bernstein Conference, 2019.
    [DOI]

  • Visualizing Deep Neural Networks for Speech Recognition with Learned Topographic Filter Maps.
    Andreas Krug & Sebastian Stober.
    In: Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2019.
    [PDF]

  • Siri visualisiert.
    Andreas Krug & Sebastian Stober.
    In: Proceedings of the 2019 NaWik Symposium Karlsruhe, Pages 24-25, 2019.

  • Deep Learning Based on Event-Related EEG Differentiates Children with ADHD from Healthy Controls.
    Amirali Vahid; Annet Bluschke; Veit Roessner; Sebastian Stober & Christian Beste.
    In: Journal of Clinical Medicine, Volume 8, Number 7, 2019.
    [DOI] [PDF]

  • Hybrid Variational Predictive Coding as a Bridge between Human and Artificial Cognition.
    André Ofner & Sebastian Stober.
    In: The 2019 Conference on Artificial Life, Number 31, Pages 68-69, 2019.
    [URL] [PDF]

  • Automatic prostate and prostate zones segmentation of magnetic resonance images using convolutional neural networks.
    Nader Aldoj; Federico Biavati; Miriam Rutz; Florian Michallek; Sebastian Stober & Marc Dewey.
    In: Proceedings of International Conference on Medical Imaging with Deep Learning (MIDL’19), 2019.
    [DOI] [PDF]

 

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