Gunnar Rtsch
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
54
Venues
20
Active years
1997–2025
Best venue rank
A*
Where they publish
Papers
54 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Preference Elicitation for Offline Reinforcement Learning. | Alize Pace, Bernhard Schlkopf, Gunnar Rtsch, Giorgia Ramponi |
| 2025 | MICCAI | Revisiting Automatic Data Curation for Vision Foundation Models in Digital Pathology. | Boqi Chen, Cdric Vincent-Cuaz, Lydia A. Schoenpflug, Manuel Madeira, Lisa Fournier, Vaishnavi Subramanian, Sonali Andani, Samuel Ruiprez-Campillo, Julia E. Vogt, Raphalle Luisier, Dorina Thanou, Viktor H. Koelzer, Pascal Frossard, Gabriele Campanella, Gunnar Rtsch |
| 2025 | WACV | Generalizable Single-Source Cross-Modality Medical Image Segmentation via Invariant Causal Mechanisms. | Boqi Chen, Yuanzhi Zhu, Yunke Ao, Sebastiano Caprara, Reto Sutter, Gunnar Rtsch, Ender Konukoglu, Anna Susmelj |
| 2024 | ICLR | Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion. | Alexandru Meterez, Amir Joudaki, Francesco Orabona, Alexander Immer, Gunnar Rtsch, Hadi Daneshmand |
| 2024 | ICLR | Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding. | Alize Pace, Hugo Yche, Bernhard Schlkopf, Gunnar Rtsch, Guy Tennenholtz |
| 2024 | ICML | Improving Neural Additive Models with Bayesian Principles. | Kouroche Bouchiat, Alexander Immer, Hugo Yche, Gunnar Rtsch, Vincent Fortuin |
| 2023 | ICML | Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels. | Alexander Immer, Tycho F. A. van der Ouderaa, Mark van der Wilk, Gunnar Rtsch, Bernhard Schlkopf |
| 2023 | ICML | Temporal Label Smoothing for Early Event Prediction. | Hugo Yche, Alize Pace, Gunnar Rtsch, Rita Kuznetsova |
| 2022 | AISTATS | Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization. | Gideon Dresdner, Maria-Luiza Vladarean, Gunnar Rtsch, Francesco Locatello, Volkan Cevher, Alp Yurtsever |
| 2022 | ICLR | Bayesian Neural Network Priors Revisited. | Vincent Fortuin, Adri Garriga-Alonso, Sebastian W. Ober, Florian Wenzel, Gunnar Rtsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison |
| 2022 | RECOMB | Lossless Indexing with Counting de Bruijn Graphs. | Mikhail Karasikov, Harun Mustafa, Gunnar Rtsch, Andr Kahles |
| 2021 | AISTATS | Scalable Gaussian Process Variational Autoencoders. | Metod Jazbec, Matthew Ashman, Vincent Fortuin, Michael Pearce, Stephan Mandt, Gunnar Rtsch |
| 2021 | ICML | Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning. | Alexander Immer, Matthias Bauer, Vincent Fortuin, Gunnar Rtsch, Mohammad Emtiyaz Khan |
| 2021 | ICML | Neighborhood Contrastive Learning Applied to Online Patient Monitoring. | Hugo Yche, Gideon Dresdner, Francesco Locatello, Matthias Hser, Gunnar Rtsch |
| 2021 | IJCAI | Boosting Variational Inference With Locally Adaptive Step-Sizes. | Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rtsch |
| 2020 | AAAI | A Commentary on the Unsupervised Learning of Disentangled Representations. | Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rtsch, Sylvain Gelly, Bernhard Schlkopf, Olivier Bachem |
| 2020 | AISTATS | GP-VAE: Deep Probabilistic Time Series Imputation. | Vincent Fortuin, Dmitry Baranchuk, Gunnar Rtsch, Stephan Mandt |
| 2020 | ICLR | Disentangling Factors of Variations Using Few Labels. | Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rtsch, Bernhard Schlkopf, Olivier Bachem |
| 2020 | ICML | Weakly-Supervised Disentanglement Without Compromises. | Francesco Locatello, Ben Poole, Gunnar Rtsch, Bernhard Schlkopf, Olivier Bachem, Michael Tschannen |
| 2020 | RECOMB | AStarix: Fast and Optimal Sequence-to-Graph Alignment. | Pesho Ivanov, Benjamin Bichsel, Harun Mustafa, Andr Kahles, Gunnar Rtsch, Martin T. Vechev |
| 2019 | ICLR | SOM-VAE: Interpretable Discrete Representation Learning on Time Series. | Vincent Fortuin, Matthias Hser, Francesco Locatello, Heiko Strathmann, Gunnar Rtsch |
| 2019 | ICLR | Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. | Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rtsch, Sylvain Gelly, Bernhard Schlkopf, Olivier Bachem |
| 2019 | ICML | Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. | Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rtsch, Sylvain Gelly, Bernhard Schlkopf, Olivier Bachem |
| 2019 | RECOMB | Sparse Binary Relation Representations for Genome Graph Annotation. | Mikhail Karasikov, Harun Mustafa, Amir Joudaki, Sara Javadzadeh-No, Gunnar Rtsch, Andr Kahles |
| 2018 | AISTATS | Boosting Variational Inference: an Optimization Perspective. | Francesco Locatello, Rajiv Khanna, Joydeep Ghosh, Gunnar Rtsch |
| 2018 | AMIA | A Machine Learning-based Early Warning System for Circulatory System Deterioration in Intensive Care Unit Patients. | Stephanie L. Hyland, Martin Faltys, Matthias Hser, Xinrui Lyu, Cristbal Esteban, Gunnar Rtsch, Tobias Merz |
| 2018 | ICLR | Clustering Meets Implicit Generative Models. | Francesco Locatello, Damien Vincent, Ilya O. Tolstikhin, Gunnar Rtsch, Sylvain Gelly, Bernhard Schlkopf |
| 2018 | ICML | On Matching Pursuit and Coordinate Descent. | Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rtsch, Bernhard Schlkopf, Sebastian U. Stich, Martin Jaggi |
| 2018 | IJCAI | Predicting circulatory system deterioration in intensive care unit patients. | Stephanie L. Hyland, Matthias Hser, Xinrui Lyu, Martin Faltys, Tobias Merz, Gunnar Rtsch |
| 2017 | AAAI | Learning Unitary Operators with Help From u(n). | Stephanie L. Hyland, Gunnar Rtsch |
| 2016 | AAAI | A Generative Model of Words and Relationships from Multiple Sources. | Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rtsch |
| 2015 | PSB | Session Introduction. | Sren Brunak, Francisco M. de la Vega, Adam A. Margolin, Benjamin J. Raphael, Gunnar Rtsch, Joshua M. Stuart |
| 2015 | PSB | Integrative Genome-wide Analysis of the Determinants of RNA Splicing in Kidney Renal Clear Cell Carcinoma. | Kjong-Van Lehmann, Andr Kahles, Cyriac Kandoth, William Lee, Nikolaus Schultz, Oliver Stegle, Gunnar Rtsch |
| 2014 | PSB | Session Introduction. | Sren Brunak, Francisco M. de la Vega, Gunnar Rtsch, Joshua M. Stuart |
| 2013 | ICDM | An Empirical Analysis of Topic Modeling for Mining Cancer Clinical Notes. | Katherine Redfield Chan, Xinghua Lou, Theofanis Karaletsos, Christopher Crosbie, Stuart M. Gardos, David Artz, Gunnar Rtsch |
| 2010 | RECOMB | Leveraging Sequence Classification by Taxonomy-Based Multitask Learning. | Christian Widmer, Jose Leiva, Yasemin Altun, Gunnar Rtsch |
| 2008 | ECCB | Optimal spliced alignments of short sequence reads. | Fabio De Bona, Stephan Ossowski, Korbinian Schneeberger, Gunnar Rtsch |
| 2008 | ISMB | POIMs: positional oligomer importance matrices - understanding support vector machine-based signal detectors. | Sren Sonnenburg, Alexander Zien, Petra Philips, Gunnar Rtsch |
| 2008 | PSB | Transcript Normalization and Segmentation of Tiling Array Data. | Georg Zeller, Stefan R. Henz, Sascha Laubinger, Detlef Weigel, Gunnar Rtsch |
| 2006 | ALT | Solving Semi-infinite Linear Programs Using Boosting-Like Methods. | Gunnar Rtsch |
| 2006 | DIS | The Solution of Semi-Infinite Linear Programs Using Boosting-Like Methods. | Gunnar Rtsch |
| 2006 | ICML | Totally corrective boosting algorithms that maximize the margin. | Manfred K. Warmuth, Jun Liao, Gunnar Rtsch |
| 2006 | ISMB | ARTS: accurate recognition of transcription starts in human. | Sren Sonnenburg, Alexander Zien, Gunnar Rtsch |
| 2005 | ICML | Large scale genomic sequence SVM classifiers. | Sren Sonnenburg, Gunnar Rtsch, Bernhard Schlkopf |
| 2005 | ISMB | RASE: recognition of alternatively spliced exons in | Gunnar Rtsch, Sren Sonnenburg, Bernhard Schlkopf |
| 2005 | RECOMB | Learning Interpretable SVMs for Biological Sequence Classification. | Sren Sonnenburg, Gunnar Rtsch, Christin Schfer |
| 2003 | Interspeech | Robust multi-class boosting. | Gunnar Rtsch |
| 2002 | COLT | Maximizing the Margin with Boosting. | Gunnar Rtsch, Manfred K. Warmuth |
| 2002 | ICANN | New Methods for Splice Site Recognition. | Sren Sonnenburg, Gunnar Rtsch, Arun K. Jagota, Klaus-Robert Mller |
| 2001 | ICANN | Learning to Predict the Leave-One-Out Error of Kernel Based Classifiers. | Koji Tsuda, Gunnar Rtsch, Sebastian Mika, Klaus-Robert Mller |
| 2000 | COLT | Barrier Boosting. | Gunnar Rtsch, Manfred K. Warmuth, Sebastian Mika, Takashi Onoda, Steven Lemm, Klaus-Robert Mller |
| 2000 | PAKDD | Robust Ensemble Learning for Data Mining. | Gunnar Rtsch, Bernhard Schlkopf, Alexander J. Smola, Sebastian Mika, Takashi Onoda, Klaus-Robert Mller |
| 1998 | ICONIP | An Improvement of AdaBoost to Avoid Overfitting. | Gunnar Rtsch, Takashi Onoda, Klaus-Robert Mller |
| 1997 | ICANN | Predicting Time Series with Support Vector Machines. | Klaus-Robert Mller, Alexander J. Smola, Gunnar Rtsch, Bernhard Schlkopf, Jens Kohlmorgen, Vladimir Vapnik |