Laura Manduchi

According to our database, Laura Manduchi authored at least 16 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

On the Challenges and Opportunities in Generative AI.

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

CoRR, 2024

2023

Challenges and Perspectives in Deep Generative Modeling (Dagstuhl Seminar 23072).

Vincent Fortuin, Yingzhen Li, Kevin Murphy, Stephan Mandt, Laura Manduchi

Dagstuhl Reports, February, 2023

Weakly supervised inference of personalized heart meshes based on echocardiography videos.

Fabian Laumer, Mounir Amrani, Laura Manduchi, Ami Beuret, Lena Rubi, Alina Dubatovka, Christian M. Matter, Joachim M. Buhmann

Medical Image Anal., 2023

Signal Is Harder To Learn Than Bias: Debiasing with Focal Loss.

Moritz Vandenhirtz, Laura Manduchi, Ricards Marcinkevics, Julia E. Vogt

CoRR, 2023

Tree Variational Autoencoders.

Laura Manduchi, Moritz Vandenhirtz, Alain Ryser, Julia E. Vogt

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Group Importance using the Differentiable Hypergeometric Distribution.

Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E. Vogt

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Interpretable Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models.

Alain Ryser, Laura Manduchi, Fabian Laumer, Holger Michel, Sven Wellmann, Julia E. Vogt

CoRR, 2022

Continuous Relaxation For The Multivariate Non-Central Hypergeometric Distribution.

Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E. Vogt

CoRR, 2022

Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models.

Alain Ryser, Laura Manduchi, Fabian Laumer, Holger Michel, Sven Wellmann, Julia E. Vogt

Proceedings of the Machine Learning for Healthcare Conference, 2022

A Deep Variational Approach to Clustering Survival Data.

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

Proceedings of the Tenth International Conference on Learning Representations, 2022

Interpretable Prediction of Pulmonary Hypertension in Newborns Using Echocardiograms.

Hanna Ragnarsdóttir, Laura Manduchi, Holger Michel, Fabian Laumer, Sven Wellmann, Ece Ozkan, Julia E. Vogt

Proceedings of the Pattern Recognition, 2022

2021

A Deep Variational Approach to Clustering Survival Data.

Laura Manduchi, Ricards Marcinkevics, Michela Carlotta Massi, Verena Gotta, Timothy Müller, Flavio Vasella, Marian C. Neidert, Marc Pfister, Julia E. Vogt

CoRR, 2021

Deep Conditional Gaussian Mixture Model for Constrained Clustering.

Laura Manduchi, Kieran Chin-Cheong, Holger Michel, Sven Wellmann, Julia E. Vogt

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

T-DPSOM: an interpretable clustering method for unsupervised learning of patient health states.

Laura Manduchi, Matthias Hüser, Martin Faltys, Julia E. Vogt, Gunnar Rätsch, Vincent Fortuin

Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

2020

DeepHeartBeat: Latent trajectory learning of cardiac cycles using cardiac ultrasounds.

Fabian Laumer, Gabriel Fringeli, Alina Dubatovka, Laura Manduchi, Joachim M. Buhmann

Proceedings of the Machine Learning for Health Workshop, 2020

2019

Variational PSOM: Deep Probabilistic Clustering with Self-Organizing Maps.

Laura Manduchi, Matthias Hüser, Gunnar Rätsch, Vincent Fortuin

CoRR, 2019