Learning Aerial Image Segmentation From Online Maps von Kaiser, Pascal, Wegner, Jan Dirk, Lucchi, Aurelien, Jaggi, Martin, Hofmann, Thomas, Schindler, Konrad

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Assessment of Fatigue Using Wearable Sensors: A Pilot Study von Luo, Hongyu, Lee, Pierre-Alexandre, Clay, Ieuan, Jaggi, Martin, De Luca, Valeria

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MyThisYourThat for interpretable identification of systematic bias in federated learning for biomedical images von Naumova, Klavdiia, Devos, Arnout, Karimireddy, Sai Praneeth, Jaggi, Martin, Hartley, Mary-Anne

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Predicting Changes in Depression Severity Using the PSYCHE-D (Prediction of Severity Change-Depression) Model Involving Person-Generated Health Data: Longitudinal Case-Control Obse... von Makhmutova, Mariko, Kainkaryam, Raghu, Ferreira, Marta, Min, Jae, Jaggi, Martin, Clay, Ieuan

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Deep learning diagnostic and risk-stratification pattern detection for COVID-19 in digital lung auscultations: clinical protocol for a case-control and prospective cohort study von Glangetas, Alban, Hartley, Mary-Anne, Cantais, Aymeric, Courvoisier, Delphine S, Rivollet, David, Shama, Deeksha M, Perez, Alexandre, Spechbach, Hervé, Trombert, Véronique, Bourquin, Stéphane, Jaggi, Martin, Barazzone-Argiroffo, Constance, Gervaix, Alain, Siebert, Johan N

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High-speed identification of suspended carbon nanotubes using Raman spectroscopy and deep learning von Zhang, Jian, Perrin, Mickael L., Barba, Luis, Overbeck, Jan, Jung, Seoho, Grassy, Brock, Agal, Aryan, Muff, Rico, Brönnimann, Rolf, Haluska, Miroslav, Roman, Cosmin, Hierold, Christofer, Jaggi, Martin, Calame, Michel

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DeepBreath—automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries von Heitmann, Julien, Glangetas, Alban, Doenz, Jonathan, Dervaux, Juliane, Shama, Deeksha M., Garcia, Daniel Hinjos, Benissa, Mohamed Rida, Cantais, Aymeric, Perez, Alexandre, Müller, Daniel, Chavdarova, Tatjana, Ruchonnet-Metrailler, Isabelle, Siebert, Johan N., Lacroix, Laurence, Jaggi, Martin, Gervaix, Alain, Hartley, Mary-Anne

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Approximating parameterized convex optimization problems von Giesen, Joachim, Jaggi, Martin, Laue, Sören

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What If…? Pandemic policy-decision-support to guide a cost-benefit-optimised, country-specific response von Mannarini, Giorgio, Posa, Francesco, Bossy, Thierry, Massemin, Lucas, Fernandez-Castanon, Javier, Chavdarova, Tatjana, Cañas, Pablo, Gupta, Prakhar, Jaggi, Martin, Hartley, Mary-Anne

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Optimal Affine-Invariant Smooth Minimization Algorithms von d'Aspremont, Alexandre, Guzmán, Cristóbal, Jaggi, Martin

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An exponential lower bound on the complexity of regularization paths von Bernd Gärtner, Martin Jaggi, Clément Maria

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Forecasting intracranial hypertension using multi-scale waveform metrics von Hüser, Matthias, Kündig, Adrian, Karlen, Walter, De Luca, Valeria, Jaggi, Martin

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Accounting for the Environment: More Talk and Little Progress von Martin Freedman, Bikki Jaggi, Martin Freedman, Bikki Jaggi

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Hypercholesterolemia Exacerbates Virus-Induced Immunopathologic Liver Disease Via Suppression of Antiviral Cytotoxic T Cell Responses von Ludewig, Burkhard, Jaggi, Martin, Dumrese, Tilman, Brduscha-Riem, Karin, Odermatt, Bernhard, Hengartner, Hans, Zinkernagel, Rolf M

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Modular Clinical Decision Support Networks (MoDN)-Updatable, interpretable, and portable predictions for evolving clinical environments von Trottet, Cécile, Vogels, Thijs, Keitel, Kristina, Kulinkina, Alexandra V, Tan, Rainer, Cobuccio, Ludovico, Jaggi, Martin, Hartley, Mary-Anne

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Generalization under Model Mismatch and Distributed Learning von Hellkvist, Martin

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Irreducible Curriculum for Language Model Pretraining von Fan, Simin, Jaggi, Martin

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Multiplication-Free Transformer Training via Piecewise Affine Operations von Kosson, Atli, Jaggi, Martin

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Linking Immune-Mediated Arterial Inflammation and Cholesterol-Induced Atherosclerosis in a Transgenic Mouse Model von Ludewig, Burkhard, Freigang, Stefan, Jaggi, Martin, Kurrer, Michael O., Pei, Yao-Chang, Vlk, Lenka, Odermatt, Bernhard, Zinkernagel, Rolf M., Hengartner, Hans

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Landmark Attention: Random-Access Infinite Context Length for Transformers von Mohtashami, Amirkeivan, Jaggi, Martin

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