Vogt, Julia E

62 publications

MIDL 2026 RadVLM-GRPO: Enhancing Chest X-Ray Report Generation and Visual Grounding via Reinforcement Learning Benjamin Gundersen, Nicolas Deperrois, Samuel Ruiperez-Campillo, Thomas M. Sutter, Julia E. Vogt, Michael Moor, Farhad Nooralahzadeh, Michael Krauthammer

TMLR 2026 Structure Is Supervision: Multiview Masked Autoencoders for Radiology Sonia Laguna, Andrea Agostini, Alain Ryser, Samuel Ruiperez-Campillo, Irene Cannistraci, Moritz Vandenhirtz, Stephan Mandt, Nicolas Deperrois, Farhad Nooralahzadeh, Michael Krauthammer, Thomas M. Sutter, Julia E Vogt

TMLR 2026 TOAST: Transformer Optimization Using Adaptive and Simple Transformations Irene Cannistraci, Simone Antonelli, Emanuele Palumbo, Thomas M. Sutter, Emanuele Rodolà, Bastian Rieck, Julia E Vogt

TMLR 2026 You Only Train Once: Differentiable Subset Selection for Omics Data Daphné Chopard, Jorge da Silva Gonçalves, Irene Cannistraci, Thomas M. Sutter, Julia E Vogt

ICLRW 2025 Beyond Glucose-Only Assessment: Advancing Nocturnal Hypoglycemia Prediction in Children with Type 1 Diabetes Marco Voegeli, Sonia Laguna, Heike Leutheuser, Marie-Anne Burckhardt, Julia E Vogt

ICLR 2025 Cross-Entropy Is All You Need to Invert the Data Generating Process Patrik Reizinger, Alice Bizeul, Attila Juhos, Julia E Vogt, Randall Balestriero, Wieland Brendel, David Klindt

ICML 2025 From Logits to Hierarchies: Hierarchical Clustering Made Simple Emanuele Palumbo, Moritz Vandenhirtz, Alain Ryser, Imant Daunhawer, Julia E Vogt

ICML 2025 From Pixels to Perception: Interpretable Predictions via Instance-Wise Grouped Feature Selection Moritz Vandenhirtz, Julia E Vogt

ICLRW 2025 Measuring Leakage in Concept-Based Methods: An Information Theoretic Approach Mikael Makonnen, Moritz Vandenhirtz, Sonia Laguna, Julia E Vogt

TMLR 2025 On the Challenges and Opportunities in Generative AI Laura Manduchi, Clara Meister, 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 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

TMLR 2025 On the Properties and Estimation of Pointwise Mutual Information Profiles Paweł Czyż, Frederic Grabowski, Julia E Vogt, Niko Beerenwinkel, Alexander Marx

MLHC 2025 PhenoRAG: Retrieval-Augmented Generation for Efficient Zero-Shot Phenotype Identification in Clinical Reports Marc Berndt, Andrea Agostini, Beatrice Stocker, Maria Padrutt, Silvio Daniel Brugger, D Sean Froese, Daphné Chopard, Julia E Vogt

ICLRW 2025 Predicting Pulmonary Hypertension in Newborns: A Multi-View VAE Approach Lucas Erlacher, Samuel Ruiperez-Campillo, Holger Michel, Sven Wellmann, Thomas M. Sutter, Ece Ozkan, Julia E Vogt

ICLRW 2025 Towards Scalable Newborn Screening: Automated General Movement Assessment in Uncontrolled Settings Daphné Chopard, Sonia Laguna, Kieran Chin-Cheong, Annika Dietz, Anna Badura, Sven Wellmann, Julia E Vogt

MLHC 2025 Towards Scalable Newborn Screening: Automated General Movement Assessment in Uncontrolled Settings Daphné Chopard, Sonia Laguna, Kieran Chin-Cheong, Annika Dietz, Anna Badura, Sven Wellmann, Julia E Vogt

ECML-PKDD 2025 TreeDiffusion: Hierarchical Generative Clustering for Conditional Diffusion Jorge da Silva Goncalves, Laura Manduchi, Moritz Vandenhirtz, Julia E. Vogt

TMLR 2025 Two Is Better than One: Aligned Representation Pairs for Anomaly Detection Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E Vogt

ICML 2025 scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data Olga Ovcharenko, Florian Barkmann, Philip Toma, Imant Daunhawer, Julia E Vogt, Sebastian Schelter, Valentina Boeva

NeurIPSW 2024 Benchmarking Self-Supervised Learning for Single-Cell Data Philip Toma, Olga Ovcharenko, Imant Daunhawer, Julia E Vogt, Florian Barkmann, Valentina Boeva

NeurIPS 2024 Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable? Sonia Laguna, Ričards Marcinkevičs, Moritz Vandenhirtz, Julia E. Vogt

NeurIPSW 2024 DIETing: Self-Supervised Learning with Instance Discrimination Learns Identifiable Features Attila Juhos, Alice Bizeul, Patrik Reizinger, Randall Balestriero, David Klindt, Mark Ibrahim, Julia E Vogt, Wieland Brendel

NeurIPSW 2024 DIETing: Self-Supervised Learning with Instance Discrimination Learns Identifiable Features Attila Juhos, Alice Bizeul, Patrik Reizinger, David Klindt, Randall Balestriero, Mark Ibrahim, Julia E Vogt, Wieland Brendel

ICLR 2024 Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders Emanuele Palumbo, Laura Manduchi, Sonia Laguna, Daphné Chopard, Julia E Vogt

NeurIPSW 2024 Exploiting Interpretable Capabilities with Concept-Enhanced Diffusion and Prototype Networks Alba Carballo-Castro, Sonia Laguna, Moritz Vandenhirtz, Julia E Vogt

NeurIPSW 2024 Exploiting Interpretable Capabilities with Concept-Enhanced Diffusion and Prototype Networks Alba Carballo-Castro, Sonia Laguna, Moritz Vandenhirtz, Julia E Vogt

NeurIPSW 2024 Exploiting Interpretable Capabilities with Concept-Enhanced Diffusion and Prototype Networks Alba Carballo-Castro, Sonia Laguna, Moritz Vandenhirtz, Julia E Vogt

NeurIPSW 2024 Learning Symmetric Contexts for Anomaly Detection Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E Vogt

NeurIPS 2024 Stochastic Concept Bottleneck Models Moritz Vandenhirtz, Sonia Laguna, Ričards Marcinkevičs, Julia E. Vogt

ICMLW 2024 Stochastic Concept Bottleneck Models Moritz Vandenhirtz, Sonia Laguna, Ričards Marcinkevičs, Julia E Vogt

ICMLW 2024 Stochastic Concept Bottleneck Models Moritz Vandenhirtz, Sonia Laguna, Ričards Marcinkevičs, Julia E Vogt

ICMLW 2024 Structured Generations: Using Hierarchical Clusters to Guide Diffusion Models Jorge da Silva Gonçalves, Laura Manduchi, Moritz Vandenhirtz, Julia E Vogt

NeurIPSW 2024 Two Is Better than One: Aligned Clusters Improve Anomaly Detection Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E Vogt

NeurIPS 2024 Unity by Diversity: Improved Representation Learning for Multimodal VAEs Thomas M. Sutter, Yang Meng, Andrea Agostini, Daphné Chopard, Norbert Fortin, Julia E. Vogt, Babak Shahbaba, Stephan Mandt

ICMLW 2024 scTree: Discovering Cellular Hierarchies in the Presence of Batch Effects in scRNA-Seq Data Moritz Vandenhirtz, Florian Barkmann, Laura Manduchi, Julia E Vogt, Valentina Boeva

ICMLW 2024 scTree: Discovering Cellular Hierarchies in the Presence of Batch Effects in scRNA-Seq Data Moritz Vandenhirtz, Florian Barkmann, Laura Manduchi, Julia E Vogt, Valentina Boeva

ICMLW 2023 (Un)reasonable Allure of Ante-Hoc Interpretability for High-Stakes Domains: Transparency Is Necessary but Insufficient for Comprehensibility Kacper Sokol, Julia E Vogt

ICMLW 2023 Deep Generative Clustering with Multimodal Variational Autoencoders Emanuele Palumbo, Sonia Laguna, Daphné Chopard, Julia E Vogt

ICMLW 2023 Deep Generative Clustering with Multimodal Variational Autoencoders Emanuele Palumbo, Sonia Laguna, Daphné Chopard, Julia E Vogt

ICMLW 2023 Differentiable Set Partitioning Thomas M. Sutter, Alain Ryser, Joram Liebeskind, Julia E Vogt

ICLR 2023 How Robust Is Unsupervised Representation Learning to Distribution Shift? Yuge Shi, Imant Daunhawer, Julia E Vogt, Philip Torr, Amartya Sanyal

ICLR 2023 Identifiability Results for Multimodal Contrastive Learning Imant Daunhawer, Alice Bizeul, Emanuele Palumbo, Alexander Marx, Julia E Vogt

ICLR 2023 Learning Group Importance Using the Differentiable Hypergeometric Distribution Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E Vogt

ICLR 2023 MMVAE+: Enhancing the Generative Quality of Multimodal VAEs Without Compromises Emanuele Palumbo, Imant Daunhawer, Julia E Vogt

ICML 2023 On the Identifiability and Estimation of Causal Location-Scale Noise Models Alexander Immer, Christoph Schultheiss, Julia E Vogt, Bernhard Schölkopf, Peter Bühlmann, Alexander Marx

ICLRW 2023 Self-Supervised Learning to Predict Ejection Fraction Using Motion-Mode Images Yurong Hu, Thomas M. Sutter, Ece Ozkan, Julia E Vogt

ICMLW 2023 Tree Variational Autoencoders Laura Manduchi, Moritz Vandenhirtz, Alain Ryser, Julia E Vogt

ICMLW 2023 Tree Variational Autoencoders Laura Manduchi, Moritz Vandenhirtz, Alain Ryser, Julia E Vogt

ICMLW 2023 Uncovering Latent Structure Using Random Partition Models Thomas M. Sutter, Alain Ryser, Joram Liebeskind, Julia E Vogt

ICLR 2022 A Deep Variational Approach to Clustering Survival Data Laura Manduchi, Ričards Marcinkevičs, Michela C. Massi, Thomas Weikert, Alexander Sauter, Verena Gotta, Timothy Müller, Flavio Vasella, Marian C. Neidert, Marc Pfister, Bram Stieltjes, Julia E Vogt

MLHC 2022 Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models Alain Ryser, Laura Manduchi, Fabian Laumer, Holger Michel, Sven Wellmann, Julia E. Vogt

ICLRW 2022 Continuous Relaxation for the Multivariate Noncentral Hypergeometric Distribution Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E Vogt

MLHC 2022 Debiasing Deep Chest X-Ray Classifiers Using Intra- and Post-Processing Methods Ricards Marcinkevics, Ece Ozkan, Julia E. Vogt

ICMLW 2022 How Robust Are Pre-Trained Models to Distribution Shift? Yuge Shi, Imant Daunhawer, Julia E Vogt, Philip Torr, Amartya Sanyal

ICMLW 2022 How Robust Are Pre-Trained Models to Distribution Shift? Yuge Shi, Imant Daunhawer, Julia E Vogt, Philip Torr, Amartya Sanyal

ICLRW 2022 MMVAE+: Enhancing the Generative Quality of Multimodal VAEs Without Compromises Emanuele Palumbo, Imant Daunhawer, Julia E Vogt

ICLR 2022 On the Limitations of Multimodal VAEs Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong, Emanuele Palumbo, Julia E Vogt

ICLR 2021 Generalized Multimodal ELBO Thomas M. Sutter, Imant Daunhawer, Julia E Vogt

ICLR 2021 Interpretable Models for Granger Causality Using Self-Explaining Neural Networks Ričards Marcinkevičs, Julia E Vogt

NeurIPSW 2021 On the Limitations of Multimodal VAEs Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong, Emanuele Palumbo, Julia E Vogt

MLJ 2015 Probabilistic Clustering of Time-Evolving Distance Data Julia E. Vogt, Marius Kloft, Stefan Stark, Sudhir Raman, Sandhya Prabhakaran, Volker Roth, Gunnar Rätsch

ICML 2012 A Complete Analysis of the L_1, P Group-Lasso Julia E. Vogt, Volker Roth

ICML 2010 The Translation-Invariant Wishart-Dirichlet Process for Clustering Distance Data Julia E. Vogt, Sandhya Prabhakaran, Thomas J. Fuchs, Volker Roth