MH
Marina M. -C. Höhne
cs.LGcs.AIcs.CVstat.MLcs.CRcs.CLcs.ROeess.IVbioinformaticsBiowaste fermentation
On Valency
published · living versionsW_jcggqfpq·v1 · currentpublished
Batch-Invariant Spectral Intelligence for Robust and Explainable Insect Authentication
with Majharulislam Babor, Giacomo Rossi, Annalisa Altavilla, Oliver Schlüter
1 version
Preprints & journals
33 papers in the corpus · 2020–2026Predicting the seed microbiome using phylogeny-driven machine learning.42437941 · Herbinger, Julia, Ramakrishnan, Dinesh Kumar, Reißfelder, Jannik et al.2026 · 0 citationsEnvironmental microbiome. 2026;21(1)
Batch-Invariant Spectral Intelligence for Robust and Explainable Insect Authentication2606.26757v1 · Majharulislam Babor, Giacomo Rossi, Annalisa Altavilla et al.2026 · 0 citationsarXivon Valency
When Multi-Sensor Fusion Fails to Generalize: Cattle Posture Classification Under Animal-Level and Temporal Distribution Shift2606.24986v1 · Leutrim Uka, Severino Pinto, Gundula Hoffmann et al.2026 · 0 citationsarXiv
Uncertainty Gating for Cost-Aware Explainable Artificial Intelligence2603.29915v1 · Georgii Mikriukov, Gr'egoire Montavon, Marina M.-C. Hohne2026 · 0 citationsarXiv
LeafTrackNet: A Deep Learning Framework for Robust Leaf Tracking in Top-Down Plant Phenotyping2512.13130v2 · Shanghua Liu, Majharulislam Babor, Christoph Verduyn et al.2025 · 1 citationarXiv
Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework2506.15538v4 · Laura Kopf, Nils Feldhus, Kirill Bykov et al.2025 · 0 citationsarXiv
Deep Learning Meets Teleconnections: Improving S2S Predictions for European Winter Weather2504.07625v1 · Philine L. Bommer, Marlene Kretschmer, Fiona R. Spuler et al.2025 · 8 citationsarXiv
Evaluate with the Inverse: Efficient Approximation of Latent Explanation Quality Distribution2502.15403v1 · Carlos Eiras-Franco, Anna Hedstrom, Marina M.-C. Hohne2025 · 0 citationsarXiv
From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation2412.05592v1 · Kristoffer Wickstr\om, Marina Marie-Claire Hohne, Anna Hedstrom2024 · 4 citationsarXiv
Digital model of biochemical reactions in lactic acid bacterial fermentation of simple glucose and biowaste substrates.39430516 · Arefi, Arman, Sturm, Barbara, Babor, Majharulislam et al.2024 · 9 citationsHeliyon. 2024;10(19):e38791
Model Guidance via Explanations Turns Image Classifiers into Segmentation Models2407.03009v1 · Xiaoyan Yu, Jannik Franzen, Wojciech Samek et al.2024 · 0 citationsarXiv
CoSy: Evaluating Textual Explanations of Neurons2405.20331v2 · Laura Kopf, Philine Lou Bommer, Anna Hedstrom et al.2024 · 0 citationsarXiv
A Fresh Look at Sanity Checks for Saliency Maps2405.02383v1 · Anna Hedstrom, Leander Weber, Sebastian Lapuschkin et al.2024 · 13 citationsarXiv
Sanity Checks Revisited: An Exploration to Repair the Model Parameter Randomisation Test2401.06465v1 · Anna Hedstrom, Leander Weber, Sebastian Lapuschkin et al.2024 · 5 citationsarXiv
Manipulating Feature Visualizations with Gradient Slingshots2401.06122v4 · Dilyara Bareeva, Marina M.-C. Hohne, Alexander Warnecke et al.2024 · 0 citationsarXiv
Prototypical Self-Explainable Models Without Re-training2312.07822v2 · Srishti Gautam, Ahcene Boubekki, Marina M. C. Hohne et al.2023 · 0 citationsarXiv
Explainable AI in Grassland Monitoring: Enhancing Model Performance and Domain Adaptability2312.08408v1 · Shanghua Liu, Anna Hedstrom, Deepak Hanike Basavegowda et al.2023 · 0 citationsarXiv
Labeling Neural Representations with Inverse Recognition2311.13594v2 · Kirill Bykov, Laura Kopf, Shinichi Nakajima et al.2023 · 4 citations37th Conference on Neural Information Processing Systems (NeurIPS 2023)
Kidnapping Deep Learning-based Multirotors using Optimized Flying Adversarial Patches2308.00344v2 · Pia Hanfeld, Khaled Wahba, Marina M.-C. Hohne et al.2023 · 0 citationsarXiv
Flying Adversarial Patches: Manipulating the Behavior of Deep Learning-based Autonomous Multirotors2305.12859v2 · Pia Hanfeld, Marina M.-C. Hohne, Michael Bussmann et al.2023 · 1 citationarXiv
Mark My Words: Dangers of Watermarked Images in ImageNet2303.05498v1 · Kirill Bykov, Klaus-Robert Muller, Marina M.-C. Hohne2023 · 5 citationsarXiv
Finding the right XAI method -- A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science2303.00652v2 · Philine Bommer, Marlene Kretschmer, Anna Hedstrom et al.2023 · 78 citationsarXiv
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus2302.07265v2 · Anna Hedstrom, Philine Bommer, Kristoffer K. Wickstr\om et al.2023 · 9 citationsTransactions on Machine Learning Research, Volume 2023, (2023), ISSN: 2835-8856
DORA: Exploring Outlier Representations in Deep Neural Networks2206.04530v4 · Kirill Bykov, Mayukh Deb, Dennis Grinwald et al.2022 · 7 citationsPublished in Transactions on Machine Learning Research (06/2023)
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond2202.06861v3 · Anna Hedstrom, Leander Weber, Dilyara Bareeva et al.2022 · 116 citationsJournal of Machine Learning Research, Vol. 24 (2023) 1-11
Visualizing the Diversity of Representations Learned by Bayesian Neural Networks2201.10859v2 · Dennis Grinwald, Kirill Bykov, Shinichi Nakajima et al.2022 · 2 citationsPublished in Transactions on Machine Learning Research (11/2023)
Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation2201.03559v1 · Srishti Gautam, Marina M.-C. Hohne, Stine Hansen et al.2022 · 6 citationsarXiv
Self-Supervised Learning for 3D Medical Image Analysis using 3D SimCLR and Monte Carlo Dropout2109.14288v2 · Yamen Ali, Aiham Taleb, Marina M. -C. Hohne et al.2021 · 6 citationsarXiv
This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation2108.12204v1 · Srishti Gautam, Marina M.-C. Hohne, Stine Hansen et al.2021 · 46 citationsarXiv
Explaining Bayesian Neural Networks2108.10346v2 · Kirill Bykov, Marina M.-C. Hohne, Adelaida Creosteanu et al.2021 · 15 citationsarXiv
DeepCOMBI: explainable artificial intelligence for the analysis and discovery in genome-wide association studies.34296082 · Mieth, Bettina, Rozier, Alexandre, Rodriguez, Juan Antonio et al.2021 · 64 citationsNAR genomics and bioinformatics. 2021;3(3):lqab065
NoiseGrad: Enhancing Explanations by Introducing Stochasticity to Model Weights2106.10185v3 · Kirill Bykov, Anna Hedstrom, Shinichi Nakajima et al.2021 · 29 citationsarXiv
How Much Can I Trust You? -- Quantifying Uncertainties in Explaining Neural Networks2006.09000v1 · Kirill Bykov, Marina M.-C. Hohne, Klaus-Robert Muller et al.2020 · 18 citationsarXiv
Career total: at least 62 works. 33 are in this corpus.
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