Florian Wenzel
Florian Wenzel
CTO/Co-founder at Mirelo AI
Verified email at - Homepage
Cited by
Cited by
How good is the bayes posterior in deep neural networks really?
F Wenzel, K Roth, BS Veeling, J Świątkowski, L Tran, S Mandt, J Snoek, ...
ICML 2020, 2020
Hyperparameter ensembles for robustness and uncertainty quantification
F Wenzel, J Snoek, D Tran, R Jenatton
NeurIPS 2020, 2020
Bayesian neural network priors revisited
V Fortuin, A Garriga-Alonso, F Wenzel, G Rätsch, R Turner, ...
ICRL 2021, 2021
Uncertainty baselines: Benchmarks for uncertainty & robustness in deep learning
Z Nado, N Band, M Collier, J Djolonga, MW Dusenberry, S Farquhar, ...
arXiv preprint arXiv:2106.04015, 2021
Quasi-Monte Carlo Variational Inference
A Buchholz, F Wenzel, S Mandt
ICML 2018, 2018
Assaying out-of-distribution generalization in transfer learning
F Wenzel, A Dittadi, PV Gehler, CJ Simon-Gabriel, M Horn, D Zietlow, ...
NeurIPS 2022, 2022
Scalable Generalized Dynamic Topic Models
P Jähnichen, F Wenzel, M Kloft, S Mandt
AISTATS 2018, 2018
Bayesian Nonlinear Support Vector Machines for Big Data
F Wenzel, T Galy-Fajou, M Deutsch, M Kloft
ECML 2017, 2017
Efficient Gaussian process classification using Polya-Gamma data augmentation
F Wenzel, T Galy-Fajou, C Donner, M Kloft, M Opper
AAAI Conference on Artificial Intelligence 2019, 2019
Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation
T Galy-Fajou, F Wenzel, C Donner, M Opper
UAI 2019, 2019
On stein variational neural network ensembles
F D'Angelo, V Fortuin, F Wenzel
arXiv preprint arXiv:2106.10760, 2021
Are Multimodal Models Robust to Image and Text Perturbations?
J Qiu, Y Zhu, X Shi, F Wenzel, Z Tang, D Zhao, B Li, M Li
Journal of Data-centric Machine Learning Research, 2024
A data augmentation perspective on diffusion models and retrieval
MF Burg, F Wenzel, D Zietlow, M Horn, O Makansi, F Locatello, C Russell
TMLR, 2023
Sparse moes meet efficient ensembles
JU Allingham, F Wenzel, ZE Mariet, B Mustafa, J Puigcerver, N Houlsby, ...
TMLR, 2022
Sparse probit linear mixed model
S Mandt, F Wenzel, S Nakajima, J Cunningham, C Lippert, M Kloft
Machine Learning 106, 1621-1642, 2017
Deep classifiers with label noise modeling and distance awareness
V Fortuin, M Collier, F Wenzel, J Allingham, J Liu, D Tran, ...
TMLR, 2022
Distilling Ensembles Improves Uncertainty Estimates
Z Mariet, R Jenatton, F Wenzel, D Tran
Advances in Approximate Bayesian Inference (AABI), 2020
Quasi-Monte Carlo Flows
F Wenzel, A Buchholz, S Mandt
NeurIPS Bayesian Deep Learning Workshop, 2018
Leveraging sparse and shared feature activations for disentangled representation learning
M Fumero, F Wenzel, L Zancato, A Achille, E Rodolà, S Soatto, ...
NeurIPS 2023, 2023
On the challenges and opportunities in generative ai
L Manduchi, K Pandey, R Bamler, R Cotterell, S Däubener, S Fellenz, ...
arXiv preprint arXiv:2403.00025, 2024
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