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Laura Manduchi
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2020 – today
- 2024
- [j2]Hanna Ragnarsdóttir, Ece Ozkan, Holger Michel, Kieran Chin-Cheong, Laura Manduchi, Sven Wellmann, Julia E. Vogt:
Deep Learning Based Prediction of Pulmonary Hypertension in Newborns Using Echocardiograms. Int. J. Comput. Vis. 132(7): 2567-2584 (2024) - [c9]Emanuele Palumbo, Laura Manduchi, Sonia Laguna, Daphné Chopard, Julia E. Vogt:
Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders. ICLR 2024 - [i12]Laura Manduchi, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric T. Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E. Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin:
On the Challenges and Opportunities in Generative AI. CoRR abs/2403.00025 (2024) - [i11]Moritz Vandenhirtz, Florian Barkmann, Laura Manduchi, Julia E. Vogt, Valentina Boeva:
scTree: Discovering Cellular Hierarchies in the Presence of Batch Effects in scRNA-seq Data. CoRR abs/2406.19300 (2024) - [i10]Jorge da Silva Goncalves, Laura Manduchi, Moritz Vandenhirtz, Julia E. Vogt:
Structured Generations: Using Hierarchical Clusters to guide Diffusion Models. CoRR abs/2407.06124 (2024) - 2023
- [j1]Fabian Laumer, Mounir Amrani, Laura Manduchi, Ami Beuret, Lena Rubi, Alina Dubatovka, Christian M. Matter, Joachim M. Buhmann:
Weakly supervised inference of personalized heart meshes based on echocardiography videos. Medical Image Anal. 83: 102653 (2023) - [c8]Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E. Vogt:
Learning Group Importance using the Differentiable Hypergeometric Distribution. ICLR 2023 - [c7]Laura Manduchi, Moritz Vandenhirtz, Alain Ryser, Julia E. Vogt:
Tree Variational Autoencoders. NeurIPS 2023 - [i9]Moritz Vandenhirtz, Laura Manduchi, Ricards Marcinkevics, Julia E. Vogt:
Signal Is Harder To Learn Than Bias: Debiasing with Focal Loss. CoRR abs/2305.19671 (2023) - [i8]Laura Manduchi, Moritz Vandenhirtz, Alain Ryser, Julia E. Vogt:
Tree Variational Autoencoders. CoRR abs/2306.08984 (2023) - [i7]Vincent Fortuin, Yingzhen Li, Kevin Murphy, Stephan Mandt, Laura Manduchi:
Challenges and Perspectives in Deep Generative Modeling (Dagstuhl Seminar 23072). Dagstuhl Reports 13(2): 47-70 (2023) - 2022
- [c6]Hanna Ragnarsdóttir, Laura Manduchi, Holger Michel, Fabian Laumer, Sven Wellmann, Ece Ozkan, Julia E. Vogt:
Interpretable Prediction of Pulmonary Hypertension in Newborns Using Echocardiograms. GCPR 2022: 529-542 - [c5]Laura Manduchi, Ricards Marcinkevics, Michela Carlotta Massi, Thomas J. Weikert, Alexander Sauter, Verena Gotta, Timothy Müller, Flavio Vasella, Marian C. Neidert, Marc Pfister, Bram Stieltjes, Julia E. Vogt:
A Deep Variational Approach to Clustering Survival Data. ICLR 2022 - [c4]Alain Ryser, Laura Manduchi, Fabian Laumer, Holger Michel, Sven Wellmann, Julia E. Vogt:
Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models. MLHC 2022: 425-458 - [i6]Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E. Vogt:
Continuous Relaxation For The Multivariate Non-Central Hypergeometric Distribution. CoRR abs/2203.01629 (2022) - [i5]Hanna Ragnarsdóttir, Laura Manduchi, Holger Michel, Fabian Laumer, Sven Wellmann, Ece Ozkan, Julia E. Vogt:
Interpretable Prediction of Pulmonary Hypertension in Newborns using Echocardiograms. CoRR abs/2203.13038 (2022) - [i4]Alain Ryser, Laura Manduchi, Fabian Laumer, Holger Michel, Sven Wellmann, Julia E. Vogt:
Interpretable Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models. CoRR abs/2206.15316 (2022) - 2021
- [c3]Laura Manduchi, Matthias Hüser, Martin Faltys, Julia E. Vogt, Gunnar Rätsch, Vincent Fortuin:
T-DPSOM: an interpretable clustering method for unsupervised learning of patient health states. CHIL 2021: 236-245 - [c2]Laura Manduchi, Kieran Chin-Cheong, Holger Michel, Sven Wellmann, Julia E. Vogt:
Deep Conditional Gaussian Mixture Model for Constrained Clustering. NeurIPS 2021: 11303-11314 - [i3]Laura Manduchi, Ricards Marcinkevics, Michela Carlotta Massi, Verena Gotta, Timothy Müller, Flavio Vasella, Marian C. Neidert, Marc Pfister, Julia E. Vogt:
A Deep Variational Approach to Clustering Survival Data. CoRR abs/2106.05763 (2021) - [i2]Laura Manduchi, Kieran Chin-Cheong, Holger Michel, Sven Wellmann, Julia E. Vogt:
Deep Conditional Gaussian Mixture Model for Constrained Clustering. CoRR abs/2106.06385 (2021) - 2020
- [c1]Fabian Laumer, Gabriel Fringeli, Alina Dubatovka, Laura Manduchi, Joachim M. Buhmann:
DeepHeartBeat: Latent trajectory learning of cardiac cycles using cardiac ultrasounds. ML4H@NeurIPS 2020: 194-212
2010 – 2019
- 2019
- [i1]Laura Manduchi, Matthias Hüser, Gunnar Rätsch, Vincent Fortuin:
Variational PSOM: Deep Probabilistic Clustering with Self-Organizing Maps. CoRR abs/1910.01590 (2019)
Coauthor Index
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