Florian Wenzel

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 39

Top Venues

CoRR

ICML

Trans. Mach. Learn. Res.

NeurIPS

Humboldt University of Berlin, Germany (PHD)

Education History

Humboldt University of Berlin, Germany

PHD

Publications

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
On the Challenges and Opportunities in Generative AI. CoRR (2024)
Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell
A data augmentation perspective on diffusion models and retrieval. CoRR (2023)
Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
Leveraging sparse and shared feature activations for disentangled representation learning. CoRR (2023)
Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
Leveraging sparse and shared feature activations for disentangled representation learning. NeurIPS (2023)
Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries. ICML (2023)
Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell
Image retrieval outperforms diffusion models on data augmentation. Trans. Mach. Learn. Res. 2023 (2023)
Junaid Ali, Matthäus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell
Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. CoRR (2023)
Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries. CoRR (2023)
Junaid Ali, Matthäus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell
Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. AIES (2023)
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
Assaying Out-Of-Distribution Generalization in Transfer Learning. NeurIPS (2022)
Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li
Are Multimodal Models Robust to Image and Text Perturbations? CoRR (2022)
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
Sparse MoEs meet Efficient Ensembles. Trans. Mach. Learn. Res. 2022 (2022)
Florian Wenzel, Andrea Dittadi, Peter Vincent Gehler, Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, Chris Russell, Thomas Brox, Bernt Schiele, Bernhard Schölkopf, Francesco Locatello
Assaying Out-Of-Distribution Generalization in Transfer Learning. CoRR (2022)
Vincent Fortuin, Adrià Garriga-Alonso, Sebastian W. Ober, Florian Wenzel, Gunnar Rätsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison
Bayesian Neural Network Priors Revisited. ICLR (2022)
Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Zhe Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou
Deep Classifiers with Label Noise Modeling and Distance Awareness. Trans. Mach. Learn. Res. 2022 (2022)
Vincent Fortuin, Adrià Garriga-Alonso, Florian Wenzel, Gunnar Rätsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison
Bayesian Neural Network Priors Revisited. CoRR (2021)
Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou
Deep Classifiers with Label Noise Modeling and Distance Awareness. CoRR (2021)
Francesco D'Angelo, Vincent Fortuin, Florian Wenzel
On Stein Variational Neural Network Ensembles. CoRR (2021)
Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah 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
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR (2021)
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
Sparse MoEs meet Efficient Ensembles. CoRR (2021)
Théo Galy-Fajou, Florian Wenzel, Manfred Opper
Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models. CoRR (2020)
Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton
Hyperparameter Ensembles for Robustness and Uncertainty Quantification. NeurIPS (2020)
Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton
Hyperparameter Ensembles for Robustness and Uncertainty Quantification. CoRR (2020)
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
How Good is the Bayes Posterior in Deep Neural Networks Really? ICML (2020)
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
How Good is the Bayes Posterior in Deep Neural Networks Really? CoRR (2020)
Théo Galy-Fajou, Florian Wenzel, Manfred Opper
Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models. AISTATS (2020)
Florian Wenzel, Théo Galy-Fajou, Christian Donner, Marius Kloft, Manfred Opper
Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation. AAAI (2019)
Théo Galy-Fajou, Florian Wenzel, Christian Donner, Manfred Opper
Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation. UAI (2019)
Théo Galy-Fajou, Florian Wenzel, Christian Donner, Manfred Opper
Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation. CoRR (2019)
Alexander Buchholz, Florian Wenzel, Stephan Mandt
Quasi-Monte Carlo Variational Inference. ICML (2018)
Florian Wenzel, Théo Galy-Fajou, Christian Donner, Marius Kloft, Manfred Opper
Efficient Gaussian Process Classification Using Polya-Gamma Data Augmentation. CoRR (2018)
Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt
Scalable Generalized Dynamic Topic Models. CoRR (2018)
Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt
Scalable Generalized Dynamic Topic Models. AISTATS (2018)
Alexander Buchholz, Florian Wenzel, Stephan Mandt
Quasi-Monte Carlo Variational Inference. CoRR (2018)
Florian Wenzel, Théo Galy-Fajou, Matthäus Deutsch, Marius Kloft
Bayesian Nonlinear Support Vector Machines for Big Data. CoRR (2017)
Florian Wenzel, Théo Galy-Fajou, Matthäus Deutsch, Marius Kloft
Bayesian Nonlinear Support Vector Machines for Big Data. ECML/PKDD (1) (2017)
Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft
Sparse probit linear mixed model. Mach. Learn. 106 (9-10) (2017)
Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert, Marius Kloft
Separating Sparse Signals from Correlated Noise in Binary Classification. CFA@UAI (2016)
Florian Wenzel, Werner Kießling
A Preference-Driven Database Approach to Reciprocal User Recommendations in Online Social Networks. DEXA (2) (2016)
Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft
Sparse Estimation in a Correlated Probit Model. CoRR (2015)
Florian Wenzel, Werner Kießling
Aggregation and Analysis of Enriched Spatial User Models from Location-Based Social Networks. GeoRich@SIGMOD (2014)
Florian Wenzel, Dominik Köppl, Werner Kießling
Interactive Toolbox for Spatial-Textual Preference Queries. SSTD (2013)
Florian Wenzel, Markus Endres, Stefan Mandl, Werner Kießling
Complex Preference Queries Supporting Spatial Applications for User Groups. Proc. VLDB Endow. 5 (12) (2012)
Werner Kießling, Markus Endres, Florian Wenzel
The Preference SQL System - An Overview. IEEE Data Eng. Bull. 34 (2) (2011)
Florian Wenzel, Werner Kießling
Group Preferences in Social Network Services. Grundlagen von Datenbanken (2010)

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Publication Activity (10 Years)

Top Topics

Top Venues

Florian Wenzel