Wenzel, Florian

20 publications

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

DMLR 2024 Benchmarking Robustness of Multimodal Image-Text Models Under Distribution Shift Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li

TMLR 2023 Image Retrieval Outperforms Diffusion Models on Data Augmentation Max F Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell

NeurIPS 2023 Leveraging Sparse and Shared Feature Activations for Disentangled Representation Learning Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello

ICML 2023 Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava

NeurIPS 2022 Assaying Out-of-Distribution Generalization in Transfer Learning Florian Wenzel, Andrea Dittadi, Peter V. Gehler, Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, Chris Russell, Thomas Brox, Bernt Schiele, Bernhard Schölkopf, Francesco Locatello

ICLR 2022 Bayesian Neural Network Priors Revisited Vincent Fortuin, Adrià Garriga-Alonso, Sebastian W. Ober, Florian Wenzel, Gunnar Ratsch, Richard E Turner, Mark van der Wilk, Laurence Aitchison

TMLR 2022 Deep Classifiers with Label Noise Modeling and Distance Awareness Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Zhe Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou

TMLR 2022 Sparse MoEs Meet Efficient Ensembles James Urquhart Allingham, Florian Wenzel, Zelda E Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel, Vincent Fortuin, Balaji Lakshminarayanan, Jasper Snoek, Dustin Tran, Carlos Riquelme Ruiz, Rodolphe Jenatton

AISTATS 2020 Automated Augmented Conjugate Inference for Non-Conjugate Gaussian Process Models Theo Galy-Fajou, Florian Wenzel, Manfred Opper

NeurIPSW 2020 Bayesian Neural Network Priors Revisited Vincent Fortuin, Adrià Garriga-Alonso, Florian Wenzel, Gunnar Ratsch, Richard E Turner, Mark van der Wilk, Laurence Aitchison

ICML 2020 How Good Is the Bayes Posterior in Deep Neural Networks Really? Florian Wenzel, Kevin Roth, Bastiaan Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin

NeurIPS 2020 Hyperparameter Ensembles for Robustness and Uncertainty Quantification Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton

AAAI 2019 Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation Florian Wenzel, Théo Galy-Fajou, Christian Donner, Marius Kloft, Manfred Opper

UAI 2019 Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation Théo Galy-Fajou, Florian Wenzel, Christian Donner, Manfred Opper

ICML 2018 Quasi-Monte Carlo Variational Inference Alexander Buchholz, Florian Wenzel, Stephan Mandt

AISTATS 2018 Scalable Generalized Dynamic Topic Models Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt

ECML-PKDD 2017 Bayesian Nonlinear Support Vector Machines for Big Data Florian Wenzel, Théo Galy-Fajou, Matthäus Deutsch, Marius Kloft

MLJ 2017 Sparse Probit Linear Mixed Model Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft

UAI 2016 Separating Sparse Signals from Correlated Noise in Binary Classification Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert, Marius Kloft