default search action
Laura Manduchi
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [j2]Hanna Ragnarsdóttir, Ece Ozkan
, Holger Michel, Kieran Chin-Cheong, Laura Manduchi, Sven Wellmann
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 - [i13]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) - [i12]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) - [i11]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) - [i10]Jorge da Silva Goncalves, Laura Manduchi, Moritz Vandenhirtz, Julia E. Vogt:
Hierarchical Clustering for Conditional Diffusion in Image Generation. CoRR abs/2410.16910 (2024) - 2023
- [j1]Fabian Laumer
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
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
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
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
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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-28 20:32 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: