Cao, C. G. L., Javot, B., Bhattarai, S., Bierig, K., Oreshnikov, I., Volchkov, V. V. Fiber-Optic Shape Sensing Using Neural Networks Operating on Multispecklegrams IEEE Sensors Journal, 24(17):27532-27540, September 2024 (article)

DOI [BibTex]

Immer, A. Advances in Probabilistic Methods for Deep Learning ETH Zurich, Switzerland, September 2024, CLS PhD Program (phdthesis)

[BibTex]

Bizeul, A., Schölkopf, B., Allen, C. A Probabilistic Model behind Self-Supervised Learning Transactions on Machine Learning Research, September 2024 (article) To be published

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Chen*, W., Horwood*, J., Heo, J., Hernández-Lobato, J. M. Leveraging Task Structures for Improved Identifiability in Neural Network Representations Transactions on Machine Learning Research, August 2024, *equal contribution (article)

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Park, J. A Measure-Theoretic Axiomatisation of Causality and Kernel Regression University of Tübingen, Germany, July 2024 (phdthesis)

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Sajjadi, S. M. M. Enhancement and Evaluation of Deep Generative Networks with Applications in Super-Resolution and Image Generation University of Tübingen, Germany, July 2024 (phdthesis)

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Kladny, K., Kügelgen, J. V., Schölkopf, B., Muehlebach, M. Deep Backtracking Counterfactuals for Causally Compliant Explanations Transactions on Machine Learning Research, July 2024 (article)

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Stimper, V. Advancing Normalising Flows to Model Boltzmann Distributions University of Cambridge, UK, Cambridge, June 2024, (Cambridge-Tübingen-Fellowship-Program) (phdthesis)

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Schölkopf, B. Grundfragen der künstlichen Intelligenz astronomie - Das Magazin, 42, May 2024 (article)

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Zabel, S., Hennig, P., Nieselt, K. VIPurPCA: Visualizing and Propagating Uncertainty in Principal Component Analysis IEEE Transactions on Visualization and Computer Graphics, 30(4):2011-2022, April 2024 (article)

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Besserve, M., Safavi, S., Schölkopf, B., Logothetis, N. LFP transient events in macaque subcortical areas reveal network coordination across scales and structures: a simultaneous fMRI-electrophysiology study Computational and Systems Neuroscience Meeting (COSYNE), March 2024 (poster)

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Rahaman, N., Weiss, M., Wüthrich, M., Bengio, Y., Li, E., Pal, C., Schölkopf, B. Language Models Can Reduce Asymmetry in Information Markets arXiv:2403.14443, March 2024, Published as: Redesigning Information Markets in the Era of Language Models, Conference on Language Modeling (COLM) (techreport)

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Shao, K., Xu, Y., Logothetis, N., Shen, Z., Besserve, M. Koopman Spectral Analysis Uncovers the Temporal Structure of Spontaneous Neural Events Computational and Systems Neuroscience Meeting (COSYNE), March 2024 (poster)

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Mancini, M., Naeem, M. F., Xian, Y., Akata, Z. Learning Graph Embeddings for Open World Compositional Zero-Shot Learning IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(3):1545-1560, IEEE, New York, NY, March 2024 (article)

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von Kügelgen, J. Identifiable Causal Representation Learning University of Cambridge, UK, Cambridge, February 2024, (Cambridge-Tübingen-Fellowship) (phdthesis)

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Visonà, G., Bouzigon, E., Demenais, F., Schweikert, G. Network propagation for GWAS analysis: a practical guide to leveraging molecular networks for disease gene discovery Briefings in Bioinformatics, 25(2), February 2024 (article)

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Pals, M., Macke, J. H., Barak, O. Trained recurrent neural networks develop phase-locked limit cycles in a working memory task PLOS Computational Biology, 20(2), February 2024 (article)

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Peisen, F., Gerken, A., Dahm, I., Nikolaou, K., Eigentler, T., Amaral, T., Moltz, J. H., Othman, A. E., Gatidis, S. Pre-treatment 18F-FDG-PET/CT parameters as biomarkers for progression free survival, best overall response and overall survival in metastatic melanoma patients undergoing first-line immunotherapy PLOS ONE, 19(1), January 2024 (article)

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Villar, S., Hogg, D. W., Yao, W., Kevrekidis, G. A., Schölkopf, B. Towards fully covariant machine learning Transactions on Machine Learning Research, January 2024 (article)

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Gebhard, T. D., Angerhausen, D., Konrad, B. S., Alei, E., Quanz, S. P., Schölkopf, B. Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks Astronomy & Astrophysics, 681, 2024 (article)

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Tsirtsis, S., Tabibian, B., Khajehnejad, M., Singla, A., Schölkopf, B., Gomez-Rodriguez, M. Optimal Decision Making Under Strategic Behavior Management Science, 2024, Published Online (article) In press

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Mordig, M., Ratsch, G., Kahles, A. SimReadUntil for benchmarking selective sequencing algorithms on ONT devices Bioinformatics, 40, 2024 (article)

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Visonà, G., Spiller, L. M., Hahn, S., Hattingen, E., Vogl, T. J., Schweikert, G., Bankov, K., Demes, M., Reis, H., Wild, P., Zeiner, P. S., Acker, F., Sebastian, M., Wenger, K. J. Machine-Learning-Aided Prediction of Brain Metastases Development in Non-Small-Cell Lung Cancers Clinical lung cancer, 24(8):e311-e322, December 2023 (article)

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Visonà, G., Duroux, D., Miranda, L., Sükei, E., Li, Y., Borgwardt, K., Oliver, C. Multimodal learning in clinical proteomics: enhancing antimicrobial resistance prediction models with chemical information Bioinformatics, 39(12), December 2023 (article)

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Laumann, F., von Kügelgen, J., Park, J., Schölkopf, B., Barahona, M. Kernel-Based Independence Tests for Causal Structure Learning on Functional Data Entropy, 25(12), November 2023 (article)

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Kerber, B., Hepp, T., Küstner, T., Gatidis, S. Deep learning-based age estimation from clinical Computed Tomography image data of the thorax and abdomen in the adult population PLOS ONE, 18(11), November 2023 (article)

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Lei, A., Schölkopf, B., Posner, I. Variational Causal Dynamics: Discovering Modular World Models from Interventions Transactions on Machine Learning Research, November 2023 (article)

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Cao, X., Liu, W., Tsang, I. W. Data-Efficient Learning via Minimizing Hyperspherical Energy IEEE transactions on pattern analysis and machine intelligence, 45(11):13422-13437, November 2023 (article)

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Feuerecker, B., Heimer, M. M., Geyer, T., Fabritius, M. P., Gu, S., Schachtner, B., Beyer, L., Ricke, J., Gatidis, S., Ingrisch, M., Cyran, C. C. Artificial Intelligence in Oncological Hybrid Imaging Nuklearmedizin, 62(5):296-305, October 2023 (article)

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Hayoz, J., Cugno, G., Quanz, S. P., Patapis, P., Alei, E., Bonse, M. J., Dannert, F. A., Garvin, E. O., Gebhard, T. D., Konrad, B. S., Sartori, L. F. CROCODILE - Incorporating medium-resolution spectroscopy of close-in directly imaged exoplanets into atmospheric retrievals via cross-correlation Astronomy & Astrophysics, 678, October 2023 (article)

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Hupkes, D., Giulianelli, M., Dankers, V., Artetxe, M., Elazar, Y., Pimentel, T., Christodoulopoulos, C., Lasri, K., Saphra, N., Sinclair, A., Ulmer, D., Schottmann, F., Batsuren, K., Sun, K., Sinha, K., Khalatbari, L., Ryskina, M., Frieske, R., Cotterell, R., Jin, Z. A taxonomy and review of generalization research in NLP Nature Machine Intelligence, 5(10):1161-1174, October 2023 (article)

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Peisen, F., Gerken, A., Dahm, I., Nikolaou, K., Eigentler, T., Amaral, T., Moltz, J. H., Othman, A. E., Gatidis, S., Dondi, F. Can Whole-Body Baseline CT Radiomics Add Information to the Prediction of Best Response, Progression-Free Survival, and Overall Survival of Stage IV Melanoma Patients Receiving First-Line Targeted Therapy: A Retrospective Register Study Diagnostics (Basel), 13(20), October 2023 (article)

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Ke*, N. R., Bilaniuk*, O., Goyal, A., Bauer, S., Larochelle, H., Schölkopf, B., Mozer, M. C., Pal, C., Bengio, Y. Neural Causal Structure Discovery from Interventions Transactions on Machine Learning Research, September 2023, *equal contribution (article)

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Malinverno, L., Barros, V., Ghisoni, F., Visonà, G., Kern, R., Nickel, P. J., Ventura, B. E., Šimić, I., Stryeck, S., Manni, F., Ferri, C., Jean-Quartier, C., Genga, L., Schweikert, G., Lovrić, M., Rosen-Zvi, M. A historical perspective of biomedical explainable AI research Patterns, 4(9), September 2023 (article)

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Buchholz, S. Some Remarks on Identifiability of Independent Component Analysis in Restricted Function Classes Transactions on Machine Learning Research, September 2023 (article)

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Boelts, J., Harth, P., Gao, R., Udvary, D., Yáñez, F., Baum, D., Hege, H., Oberlaender, M., Macke, J. H. Simulation-based inference for efficient identification of generative models in computational connectomics PLOS Computational Biology, 19(9):1-28, September 2023 (article)

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Hawkins-Hooker, A., Visonà, G., Narendra, T., Rojas-Carulla, M., Schölkopf, B., Schweikert, G. Getting personal with epigenetics: towards individual-specific epigenomic imputation with machine learning Nature Communications, 14(1), August 2023 (article)

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Vaughan, S. R., Gebhard, T. D., Bott, K., Casewell, S. L., Cowan, N. B., Doelman, D. S., Kenworthy, M., Mazoyer, J., Millar-Blanchaer, M. A., Trees, V. J. H., Stam, D. M., Absil, O., Altinier, L., Baudoz, P., Belikov, R., Bidot, A., Birkby, J. L., Bonse, M. J., Brandl, B., Carlotti, A., Choquet, E., van Dam, D., Desai, N., Fogarty, K., Fowler, J., van Gorkom, K., Gutierrez, Y., Guyon, O., Haffert, S. Y., Herscovici-Schiller, O., Hours, A., Juanola-Parramon, R., Kleisioti, E., König, L., van Kooten, M., Krasteva, M., Laginja, I., Landman, R., Leboulleux, L., Mouillet, D., N’Diaye, M., Por, E. H., Pueyo, L., Snik, F. Chasing rainbows and ocean glints: Inner working angle constraints for the Habitable Worlds Observatory Monthly Notices of the Royal Astronomical Society, 524(4):5477-5485, August 2023 (article)

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Bonse, M. J., Garvin, E. O., Gebhard, T. D., Dannert, F. A., Cantalloube, F., Cugno, G., Absil, O., Hayoz, J., Milli, J., Kasper, M., Quanz, S. P. Comparing Apples with Apples: Robust Detection Limits for Exoplanet High-contrast Imaging in the Presence of Non-Gaussian Noise The American Astronomical Society, 166(2), July 2023 (article)

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Karimi, A. Advances in Algorithmic Recourse: Ensuring Causal Consistency, Fairness, & Robustness ETH Zurich, Switzerland, July 2023 (phdthesis)

[BibTex]

Wellnitz, D., Kekić, A., Heiss, J., Gertz, M., Weidemüller, M., Spitz, A. A network approach to atomic spectra Journal of Physics: Complexity, 4(3), July 2023 (article)

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Ortiz-Jimenez*, G., de Jorge*, P., Sanyal, A., Bibi, A., Dokania, P. K., Frossard, P., Rogez, G., Torr, P. Catastrophic overfitting can be induced with discriminative non-robust features Transactions on Machine Learning Research , July 2023, *equal contribution (article)

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Kübler, J. M. Learning and Testing Powerful Hypotheses University of Tübingen, Germany, July 2023 (phdthesis)

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Wang, Q., Sanchez, F. R., McCarthy, R., Bulens, D. C., McGuinness, K., O’Connor, N., Wüthrich, M., Widmaier, F., Bauer, S., Redmond, S. J. Dexterous robotic manipulation using deep reinforcement learning and knowledge transfer for complex sparse reward-based tasks Expert Systems, 40(6), July 2023 (article)

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Kekić, A., Dehning, J., Gresele, L., von Kügelgen, J., Priesemann, V., Schölkopf, B. Evaluating vaccine allocation strategies using simulation-assisted causal modeling Patterns, 4(6), June 2023 (article)

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Gresele, L. Learning Identifiable Representations: Independent Influences and Multiple Views University of Tübingen, Germany, June 2023 (phdthesis)

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Katiyar, P., Schwenck, J., Frauenfeld, L., Divine, M. R., Agrawal, V., Kohlhofer, U., Gatidis, S., Kontermann, R., Königsrainer, A., Quintanilla-Martinez, L., la Fougère, C., Schölkopf, B., Pichler, B. J., Disselhorst, J. A. Quantification of intratumoural heterogeneity in mice and patients via machine-learning models trained on PET–MRI data Nature Biomedical Engineering, 7(8):1014-1027, June 2023 (article)

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Badirli, S., Picard, C. J., Mohler, G., Richert, F., Akata, Z., Dundar, M. Classifying the unknown: Insect identification with deep hierarchical Bayesian learning Methods in Ecology and Evolution, 14(6):1515-1530, June 2023 (article)

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Mineeva*, O., Danciu*, D., Schölkopf, B., Ley, R. E., Rätsch, G., Youngblut, N. D. ResMiCo: Increasing the quality of metagenome-assembled genomes with deep learning PLOS Computational Biology, 19(5), Public Library of Science, San Francisco, CA, May 2023, *equal contribution (article)

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Gatidis, S., Kart, T., Fischer, M., Winzeck, S., Glocker, B., Bai, W., Bülow, R., Emmel, C., Friedrich, L., Kauczor, H., Keil, T., Kröncke, T., Mayer, P., Niendorf, T., Peters, A., Pischon, T., Schaarschmidt, B., Schmidt, B., Schulze, M., Umutle, L., Völzke, H., Küstner, T., Bamberg, F., Schölkopf, B., Rueckert, D. Better Together: Data Harmonization and Cross-StudAnalysis of Abdominal MRI Data From UK Biobank and the German National Cohort Investigative Radiology, 58(5):346-354, May 2023 (article)

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