High Dimensional Clustering with r-nets. - Georgia Avarikioti; Alain Ryser; Yuyi Wang 001; Roger Wattenhofer (AAAI, 2019)

Latency-Aware Industrial Fog Application Orchestration with Kubernetes. - Raphael Eidenbenz; Yvonne-Anne Pignolet; Alain Ryser (FMEC, 2020)

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

Continuous Relaxation For The Multivariate Non-Central Hypergeometric Distribution. - Thomas M. Sutter; Laura Manduchi; Alain Ryser; Julia E. Vogt (CoRR, 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)

Learning Group Importance using the Differentiable Hypergeometric Distribution. - Thomas M. Sutter; Laura Manduchi; Alain Ryser; Julia E. Vogt (ICLR, 2023)

Tree Variational Autoencoders. - Laura Manduchi; Moritz Vandenhirtz; Alain Ryser; Julia E. Vogt (NeurIPS, 2023)

Differentiable Random Partition Models. - Thomas M. Sutter; Alain Ryser; Joram Liebeskind; Julia E. Vogt (NeurIPS, 2023)

Can Generative AI Learn Physiological Waveform Morphologies? A Study on Denoising Intracardiac Signals in Ischemic Cardiomyopathy. - Samuel Ruipérez-Campillo; Alain Ryser; Thomas M. Sutter; Ruibin Feng; Prasanth Ganesan; Brototo Deb; Kelly A. Brennan; Maarten Z. Kolk; Fleur V. Y. Tjong; Albert J. Rogers; Sanjiv M. Narayan; Julia E. Vogt (EMBC, 2024)

Transfer Learning for Pediatric Glucose Forecasting. - Alain Ryser; Chuhao Feng; Tobias Scheithauer; Marc Pfister; Marie-Anne Burckhardt; Sara Bachmann; Alexander Marx 001; Julia E. Vogt (ML4H@NeurIPS, 2024)

Anomaly Detection by Context Contrasting. - Alain Ryser; Thomas M. Sutter; Alexander Marx 001; Julia E. Vogt (CoRR, 2024)

From Logits to Hierarchies: Hierarchical Clustering made Simple. - Emanuele Palumbo; Moritz Vandenhirtz; Alain Ryser; Imant Daunhawer; Julia E. Vogt (CoRR, 2024)

RadVLM: A Multitask Conversational Vision-Language Model for Radiology. - Nicolas Deperrois; Hidetoshi Matsuo; Samuel Ruipérez-Campillo; Moritz Vandenhirtz; Sonia Laguna; Alain Ryser; Koji Fujimoto; Mizuho Nishio; Thomas M. Sutter; Julia E. Vogt; Jonas Kluckert; Thomas Frauenfelder; et al. (CoRR, 2025)

From Pixels to Components: Eigenvector Masking for Visual Representation Learning. - Alice Bizeul; Thomas M. Sutter; Alain Ryser; Bernhard Schölkopf; Julius von Kügelgen; Julia E. Vogt (CoRR, 2025)

Leveraging the Structure of Medical Data for Improved Representation Learning. - Andrea Agostini; Sonia Laguna; Alain Ryser; Samuel Ruipérez-Campillo; Moritz Vandenhirtz; Nicolas Deperrois; Farhad Nooralahzadeh; Michael Krauthammer; Thomas M. Sutter; Julia E. Vogt (CoRR, 2025)

A Denoising VAE for Intracardiac Time Series in Ischemic Cardiomyopathy. - Samuel Ruipérez-Campillo; Alain Ryser; Thomas M. Sutter; Ruibin Feng; Prasanth Ganesan; Brototo Deb; Kelly A. Brennan; Maxime Pedron; Albert J. Rogers; Maarten Z. Kolk; Fleur V. Y. Tjong; Sanjiv M. Narayan; et al. (CoRR, 2025)