Assaying out-of-distribution generalization in transfer learning
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
NeurIPS,
2022
PDF
Deep classifiers with label noise modeling and distance awareness
Vincent Fortuin, Mark Collier, Florian Wenzel, James Allingham, Jeremiah Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou
TMLR,
2021
PDF
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
TMLR,
2021
PDF
Uncertainty baselines: Benchmarks for uncertainty & robustness in deep learning
Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W Dusenberry, Sebastian Farquhar, Qixuan Feng, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim GJ Rudner, Faris Sbahi, Yeming Wen, Florian Wenzel, Kevin Murphy, D Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran
arXiv,
2021
PDF
Code
How Good is the Bayes Posterior in Deep Neural Networks Really?
F. Wenzel*, K. Roth*, B. Veeling*, J. Świątkowski, L. Tran, S. Mandt, J. Snoek, T. Salimans, R. Jenatton, S. Nowozin
(* = equal contribution)
ICML,
2020
Oral Presentation (long)
PDF
Code
Slides
Video