Florian Wenzel

According to our database, Florian Wenzel authored at least 32 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

On the Challenges and Opportunities in Generative AI.

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

CoRR, 2024

2023

Image retrieval outperforms diffusion models on data augmentation.

Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell

Trans. Mach. Learn. Res., 2023

A data augmentation perspective on diffusion models and retrieval.

Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the International Conference on Machine Learning, 2023

Evaluating the Fairness of Discriminative Foundation Models in Computer Vision.

Junaid Ali, Matthäus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

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

Trans. Mach. Learn. Res., 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

Trans. Mach. Learn. Res., 2022

Are Multimodal Models Robust to Image and Text Perturbations?

Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Bayesian Neural Network Priors Revisited.

Vincent Fortuin, Adrià Garriga-Alonso, Sebastian W. Ober, Florian Wenzel, Gunnar Rätsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

On Stein Variational Neural Network Ensembles.

Francesco D'Angelo, Vincent Fortuin, Florian Wenzel

CoRR, 2021

Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning.

Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Z. Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran

CoRR, 2021

Bayesian Neural Network Priors Revisited.

Vincent Fortuin, Adrià Garriga-Alonso, Florian Wenzel, Gunnar Rätsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison

CoRR, 2021

2020

Scalable Inference in Latent Gaussian Process Models.

Florian Wenzel

PhD thesis, 2020

Hyperparameter Ensembles for Robustness and Uncertainty Quantification.

Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

How Good is the Bayes Posterior in Deep Neural Networks Really?

Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin

Proceedings of the 37th International Conference on Machine Learning, 2020

Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models.

Théo Galy-Fajou, Florian Wenzel, Manfred Opper

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation.

Théo Galy-Fajou, Florian Wenzel, Christian Donner, Manfred Opper

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation.

Florian Wenzel, Théo Galy-Fajou, Christian Donner, Marius Kloft, Manfred Opper

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Quasi-Monte Carlo Variational Inference.

Alexander Buchholz, Florian Wenzel, Stephan Mandt

Proceedings of the 35th International Conference on Machine Learning, 2018

Scalable Generalized Dynamic Topic Models.

Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Sparse probit linear mixed model.

Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft

Mach. Learn., 2017

Bayesian Nonlinear Support Vector Machines for Big Data.

Florian Wenzel, Théo Galy-Fajou, Matthäus Deutsch, Marius Kloft

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2016

Separating Sparse Signals from Correlated Noise in Binary Classification.

Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert, Marius Kloft

Proceedings of the UAI 2016 Workshop on Causation: Foundation to Application co-located with the 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016), 2016

A Preference-Driven Database Approach to Reciprocal User Recommendations in Online Social Networks.

Florian Wenzel, Werner Kießling

Proceedings of the Database and Expert Systems Applications, 2016

2015

Sparse Estimation in a Correlated Probit Model.

Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft

CoRR, 2015

2014

Aggregation and Analysis of Enriched Spatial User Models from Location-Based Social Networks.

Florian Wenzel, Werner Kießling

Proceedings of Workshop on Managing and Mining Enriched Geo-Spatial Data, 2014

2013

Interactive Toolbox for Spatial-Textual Preference Queries.

Florian Wenzel, Dominik Köppl, Werner Kießling

Proceedings of the Advances in Spatial and Temporal Databases, 2013

2012

Complex Preference Queries Supporting Spatial Applications for User Groups.

Florian Wenzel, Markus Endres, Stefan Mandl, Werner Kießling

Proc. VLDB Endow., 2012

2011

The Preference SQL System - An Overview.

Werner Kießling, Markus Endres, Florian Wenzel

IEEE Data Eng. Bull., 2011

2010

Group Preferences in Social Network Services.

Florian Wenzel, Werner Kießling

Proceedings of the 22nd Workshop "Grundlagen von Datenbanken 2010", Bad Helmstedt, 2010