2026
Wittenmayer, K, Rao, S, Parchami-Araghi, A, Schiele, B, Fischer, J, Insight: Interpretable Semantic Hierarchies in Vision-Language Encoders preprint: arXiv:2601.13798, 2026. [preprint] [Code]
Wittenmayer, K, Rao, S, Parchami-Araghi, A, Schiele, B, Fischer, J, Insight: Interpretable Semantic Hierarchies in Vision-Language Encoders preprint: arXiv:2601.13798, 2026. [2025
Parchami-Araghi, A, Rao, S, Fischer, J, Schiele, B, FaCT: Faithful Concept Traces for Explaining Neural Network Decisions accepted at NeurIPS 2025. (24.5% acceptence rate) [preprint] [Code]
Parchami-Araghi, A, Rao, S, Fischer, J, Schiele, B, FaCT: Faithful Concept Traces for Explaining Neural Network Decisions accepted at NeurIPS 2025. (24.5% acceptence rate) [Görgün, A, Schiele, B, Fischer, J, VITAL: More Understandable Feature Visualization through Distribution Alignment and Relevant Information Flow accepted at ICCV 2025. (24% acceptance rate) [preprint] [project page]
Hedderich, MA, Wang, A, Zhao, R, Eichin, F, Fischer, J, Plank, B, What’s the Difference? Supporting Users in Identifying the Effects of Prompt and Model Changes Through Token Patterns accepted at ACL (main conference) 2025. [preprint]
Hesse, R, Fischer, J, Schaub-Meyer, S, Roth, S, Disentangling Polysemantic Channels in Convolutional Neural Networks accepted at CVPR workshop on Mechanistic Interpretability for Vision (MIV) 2025. [preprint]
Görgün, A, Sammani, F, Deligiannis, N, Schiele, B, Fischer, J, Temporal Concept Dynamics In Diffusion Models Via Prompt-Conditioned Interventions preprint: arXiv:2512.08486 [preprint]
Zhu, J, Wu, Y, Zhu, W, Cao, J, Zheng, Y, Chen, Y, Yang, X, Schiele, B, Fischer, J, Hu, X, LayerCake: Token-Aware Contrastive Decoding within Large Language Model Layers preprint: arXiv:507.04404, 2025. [preprint]
Pham, N, Schiele, B, Kortylewski, A*, Fischer, J*, Escaping Plato’s Cave: Robust Conceptual Reasoning through Interpretable 3D Neural Object Volumes preprint: arXiv:2503.13429, 2025. [preprint] [project page] *equal contribution
Walter, NP, Vreeken, J, Fischer, J, Now you see me! A framework for obtaining class-relevant saliency maps preprint: arXiv:2503.07346, 2025. [preprint] [project page]
Sammani, F, Fischer, J, Deligiannis, N, Unlocking Open-Set Language Accessibility in Vision Models preprint: arXiv:2503.10981, 2025. [preprint]
Chen, C, Saha, E, Fischer, J, Guebila, MB, Fanfani, V, Shutta, K, Padi, M, Glass, K, DeMeo, D, Lopes-Ramos, C, Quackenbush, J, Identifying Sex Differences in Lung Adenocarcinoma Using Multi-Omics Integrative Protein Signaling Networks Biology of Sex Differences, 2025. (IF: 8.24, 2022) [preprint]
Chen, C, Saha, E, Fischer, J, Guebila, MB, Fanfani, V, Shutta, K, Padi, M, Glass, K, DeMeo, D, Lopes-Ramos, C, Quackenbush, J, Identifying Sex Differences in Lung Adenocarcinoma Using Multi-Omics Integrative Protein Signaling Networks Biology of Sex Differences, 2025. (IF: 8.24, 2022) [Fanfani, V, Shutta, KH, Mandros, P, Fischer, J, Saha, E, Micheletti, S, Chen, C, Guebila, MB, Lopes-Ramos, CM, Quackenbush, J, Reproducible processing of TCGA regulatory networks GigaScience, Oxford University Press, 2025. [Article]
Lin, Y, Breuer, K, Weichenhan, D, Lafrenz, P, Wilk, A, Chepeleva, M, Mücke, O, Schönung, M, Petermann, F, Kensche, P, Weiser, L, Thommen, F, Giacomelli, G, Nordstroem, K, Gonzales-Avalos, E, Merkel, A, Kretzmer, H, Fischer, J, Krämer, S, Iskar, M, Wolf, S, Buchhalter, I, Esteller, M, Lawerenz, C, Twardziok, S, Zapatka, M, Hovestadt, V, Schlesner, M, Schulz, M, Hoffmann, S, Gerhauser, C, Walter, J, Hartmann, M, Lipka, DB, Assenov, Y, Bock, C, Plass, C, Toth, R, Lutsik, P Pipeline Olympics: continuable benchmarking of computational workflows for DNA methylation sequencing data against an experimental gold-standard accepted at Nucleic Acid Research, Oxford University Press, 2025. (IF: 16.8, 2024) [preprint]
2024
Hossain, I‡, Fischer, J‡, Burkholz, R*, Quackenbush, J*, Pruning neural network models for gene regulatory dynamics using data and domain knowledge accepted at NeurIPS 2024. (25.8% acceptance rate, Core A*) [preprint]
‡*equal contribution
Walter, NP, Fischer, J, Vreeken, J, Finding Interpretable Class-Specific Patterns through Efficient Neural Search AAAI Conference on Artificial Intelligence (AAAI), 2024. (23.8% acceptance rate, Core A*) [Article]
Saha, E‡, Fanfani, V‡, Mandros, P, Guebila, MB, Fischer, J, Shutta, KH, Glass, K, DeMeo, DL, Lopes-Ramos, CM, Quackenbush, J, Bayesian Optimized sample-specific Networks Obtained By Omics data (BONOBO) Conference for Research in Computational Molecular Biology (RECOMB), 2024. (16.5% acceptance rate) [Conference paper]
‡equal contribution
Fischer, J, Ma, R, Sailing in high-dimensional spaces: Low-dimensional embeddings through angle preservation preprint: arXiv:2406.09876, 2024. [preprint]
Fischer, J, Shutta, KH, Chen, C, Fanfani, V, Saha, E, Mandros, P, Guebila, MB, Xiu, J, Nieva, J, Liu, S, Uprety, D, Spetzler, D, Lopes-Ramos, CM, DeMeo, D, Quackenbush, J, Selective loss of Y chromosomes in lung adenocarcinoma modulates the tumor immune environment through cancer/testis antigens bioRxiv:10.1101/2024.09.19.613876v1, 2024. [preprint]
Mandros, P, Gallagher, I, Fanfani, V, Chen, C, Fischer, J, Ismail, A, Hsu, L, Saha, E, DeConti, DK, Quackenbush, J, node2vec2rank: Large Scale and Stable Graph Differential Analysis via Multi-Layer Node Embeddings and Ranking preprint: bioRxiv:10.1101/2024.06.16.599201v1, 2024. [preprint]
Saha, E‡, Fanfani, V‡, Mandros, P, Guebila, MB, Fischer, J, Shutta, KH, Glass, K, DeMeo, DL, Lopes-Ramos, CM, Quackenbush, J, Bayesian inference of sample-specific coexpression networks Genome Research, CSHL, 2024. (IF: 6.70, 2022) [PDF]
‡equal contribution
Saha, E, Guebila, MB, Fanfani, V, Fischer, J, Shutta, KH, Mandros, P, DeMeo, DL, Quackenbush, J, Lopes-Ramos, CM, Gene regulatory Networks Reveal Sex Difference in Lung Adenocarcinoma Biology of Sex Differences 15(62), 2024. (IF: 8.24, 2022) [preprint] [Article]
Hossain, I, Fanfani, V, Fischer, J, Quackenbush, J, Burkholz, J, Biologically informed NeuralODEs for genome-wide regulatory dynamics Genome Biology 25(127), BMC, 2024. (IF: 17.4, 2022) [Article]
2023
Hedderich, M‡, Fischer, J‡, Klakow, D, Vreeken, J, Understanding and Mitigating Classification Errors Through Interpretable Token Patterns Empirical Methods in Natural Language Processing (EMNLP) BlackboxNLP workshop, 2023. [preprint]
‡equal contribution
Kamp, M, Fischer, J, Vreeken, J, Federated Learning from Small Datasets. International Conference on Learning Representations (ICLR), OpenReview, 2023. (31.8% acceptance rate, Core A*) [PDF]
Fischer, J, Burkholz, R, Vreeken, J, Preserving local densities in low-dimensional embeddings. preprint: arXiv:2301.13732, 2023. [preprint]
Fischer, J, Schulz, MH, Efficiently Quantifying DNA Methylation for Bulk- and Single-cell Bisulfite Data. Bioinformatics 39(6), Oxford University Press, 2023. (IF: 5.8, 2023) [Article]
2022
Hedderich, M‡, Fischer, J‡, Klakow, D, Vreeken, J, Label-Descriptive Patterns and their Application to Characterizing Classification Errors. In: Proceedings of the International Conference on Machine Learning (ICML), PMLR, 2022. (21.9% acceptance rate, Core A*) [PDF]
‡equal contribution
Fischer, J, Burkholz, R, Plant ‘n’ Seek: Can You Find the Winning Ticket? International Conference on Learning Representations (ICLR), OpenReview, 2022. (32.9% acceptance rate, Core A*) [PDF]
Marx, A, Fischer, J, Estimating Mutual Information via Geodesic kNN. SIAM Conference on Data Mining (SDM), SIAM, 2022. (27.9% acceptance rate, Core A) [Article]
2021
Fischer, J, Vreeken, J, Differentiable Pattern Set Mining. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2021. (15.4% acceptance rate, Core A*) [Article]
Fischer, J, Oláh, A, Vreeken, J, What’s in the Box? Explaining Neural Networks with Robust Rules. In: Proceedings of the International Conference on Machine Learning (ICML), PMLR, 2021. (21.4% acceptance rate, Core A*) [PDF]
Fischer, J, Ardakani, FB, Kattler, K, Walter, J, Schulz, MH, CpG content-dependent associations between transcription factors and histone modifications. Plos ONE 16(4): e0249985, 2021. (IF: 3.7, 2023) [Article]
Fischer, J‡, Gadhikar‡, A, Burkholz, R, Lottery Tickets with Nonzero Biases. preprint: arXiv:2110.11150, 2021. [preprint]
‡equal contribution
Heiter, E, Fischer, J, Vreeken, J, Factoring out prior knowledge from low-dimensional embeddings. preprint: arXiv:2103.01828, 2021. [preprint]
2020
Fischer, J, Vreeken, J, Discovering Succinct Pattern Sets Expressing Co-Occurrence and Mutual Exclusivity. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2020. (16.8% acceptance rate, Core A*) [Article]
2019
Fischer, J, Vreeken, J, Sets of Robust Rules, and How to Find Them In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Data (ECMLPKDD), Springer, 2019. (17.7% acceptance rate, Core A, ==selected plenary talk==, <5% of accepted papers) [Article]
2018
Ardakani, FB Kattler, K, Nordström, KJ, Gasparoni, N, Gasparoni, G, Fuchs, S, Sinha, A, Barann, M, Ebert, P, Fischer, J, Hutter, B, Zipprich, G, Imbusch, CD, Felder, B, Eils, J, Brors, B, Lengauer, T, Manke, T, Rosenstiel, P, Walter, J, Schulz, MH, Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters. Epigenetics & Chromatin 11(1): 66, 2018. (IF: 5.5, 2023) [Article]
Theses
Fischer, J, More than the sum of its parts – pattern mining, neural networks, and how they complement each other. Doctoral Dissertation, 2022. [PDF]