Florian Wenzel

48 papers A* 8A 3B 1C 1Journal 29Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	On the Challenges and Opportunities in Generative AI. Trans. Mach. Learn. Res. 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 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
2024	J	`jnl`	Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift. J. Data-centric Mach. Learn. Res. Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li
2024	J	`jnl`	On the Challenges and Opportunities in Generative AI. CoRR 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
2023	J	`jnl`	A data augmentation perspective on diffusion models and retrieval. CoRR Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell
2023	C	`conf`	Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. AIES Junaid Ali, Matthäus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell
2023	J	`jnl`	Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. CoRR Junaid Ali, Matthäus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell
2023	J	`jnl`	Image retrieval outperforms diffusion models on data augmentation. Trans. Mach. Learn. Res. Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell
2023	A*	`conf`	Leveraging sparse and shared feature activations for disentangled representation learning. NeurIPS Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
2023	J	`jnl`	Leveraging sparse and shared feature activations for disentangled representation learning. CoRR Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
2023	A*	`conf`	Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries. ICML Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava
2023	J	`jnl`	Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries. CoRR Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava
2022	J	`jnl`	Are Multimodal Models Robust to Image and Text Perturbations? CoRR Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li
2022	A*	`conf`	Assaying Out-Of-Distribution Generalization in Transfer Learning. NeurIPS 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
2022	J	`jnl`	Assaying Out-Of-Distribution Generalization in Transfer Learning. CoRR 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
2022	A*	`conf`	Bayesian Neural Network Priors Revisited. ICLR Vincent Fortuin, Adrià Garriga-Alonso, Sebastian W. Ober, Florian Wenzel, Gunnar Rätsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison
2022	J	`jnl`	Deep Classifiers with Label Noise Modeling and Distance Awareness. Trans. Mach. Learn. Res. Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Zhe Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou
2022	J	`jnl`	Sparse MoEs meet Efficient Ensembles. Trans. Mach. Learn. Res. 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
2021	J	`jnl`	Bayesian Neural Network Priors Revisited. CoRR Vincent Fortuin, Adrià Garriga-Alonso, Florian Wenzel, Gunnar Rätsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison
2021	J	`jnl`	Deep Classifiers with Label Noise Modeling and Distance Awareness. CoRR Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Z. Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou
2021	J	`jnl`	On Stein Variational Neural Network Ensembles. CoRR Francesco D'Angelo, Vincent Fortuin, Florian Wenzel
2021	J	`jnl`	Sparse MoEs meet Efficient Ensembles. CoRR 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
2021	J	`jnl`	Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR 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
2020	A	`conf`	Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models. AISTATS Théo Galy-Fajou, Florian Wenzel, Manfred Opper
2020	J	`jnl`	Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models. CoRR Théo Galy-Fajou, Florian Wenzel, Manfred Opper
2020	A*	`conf`	How Good is the Bayes Posterior in Deep Neural Networks Really? ICML Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	How Good is the Bayes Posterior in Deep Neural Networks Really? CoRR Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	A*	`conf`	Hyperparameter Ensembles for Robustness and Uncertainty Quantification. NeurIPS Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton
2020	J	`jnl`	Hyperparameter Ensembles for Robustness and Uncertainty Quantification. CoRR Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton
2020	—	`—`	Scalable Inference in Latent Gaussian Process Models. Florian Wenzel
2019	A*	`conf`	Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation. AAAI Florian Wenzel, Théo Galy-Fajou, Christian Donner, Marius Kloft, Manfred Opper
2019	A	`conf`	Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation. UAI Théo Galy-Fajou, Florian Wenzel, Christian Donner, Manfred Opper
2019	J	`jnl`	Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation. CoRR Théo Galy-Fajou, Florian Wenzel, Christian Donner, Manfred Opper
2018	J	`jnl`	Efficient Gaussian Process Classification Using Polya-Gamma Data Augmentation. CoRR Florian Wenzel, Théo Galy-Fajou, Christian Donner, Marius Kloft, Manfred Opper
2018	A*	`conf`	Quasi-Monte Carlo Variational Inference. ICML Alexander Buchholz, Florian Wenzel, Stephan Mandt
2018	J	`jnl`	Quasi-Monte Carlo Variational Inference. CoRR Alexander Buchholz, Florian Wenzel, Stephan Mandt
2018	A	`conf`	Scalable Generalized Dynamic Topic Models. AISTATS Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt
2018	J	`jnl`	Scalable Generalized Dynamic Topic Models. CoRR Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt
2017	—	`conf`	Bayesian Nonlinear Support Vector Machines for Big Data. ECML/PKDD (1) Florian Wenzel, Théo Galy-Fajou, Matthäus Deutsch, Marius Kloft
2017	J	`jnl`	Bayesian Nonlinear Support Vector Machines for Big Data. CoRR Florian Wenzel, Théo Galy-Fajou, Matthäus Deutsch, Marius Kloft
2017	J	`jnl`	Sparse probit linear mixed model. Mach. Learn. Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft
2016	—	`conf`	A Preference-Driven Database Approach to Reciprocal User Recommendations in Online Social Networks. DEXA (2) Florian Wenzel, Werner Kießling
2016	—	`conf`	Separating Sparse Signals from Correlated Noise in Binary Classification. CFA@UAI Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert, Marius Kloft
2015	J	`jnl`	Sparse Estimation in a Correlated Probit Model. CoRR Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft
2014	—	`conf`	Aggregation and Analysis of Enriched Spatial User Models from Location-Based Social Networks. GeoRich@SIGMOD Florian Wenzel, Werner Kießling
2013	B	`conf`	Interactive Toolbox for Spatial-Textual Preference Queries. SSTD Florian Wenzel, Dominik Köppl, Werner Kießling
2012	J	`jnl`	Complex Preference Queries Supporting Spatial Applications for User Groups. Proc. VLDB Endow. Florian Wenzel, Markus Endres, Stefan Mandl, Werner Kießling
2011	J	`jnl`	The Preference SQL System - An Overview. IEEE Data Eng. Bull. Werner Kießling, Markus Endres, Florian Wenzel
2010	—	`conf`	Group Preferences in Social Network Services. Grundlagen von Datenbanken Florian Wenzel, Werner Kießling