Подписаться
Florian Stimberg
Florian Stimberg
DeepMind
Подтвержден адрес электронной почты в домене google.com
Название
Процитировано
Процитировано
Год
Efficient neural audio synthesis
N Kalchbrenner, E Elsen, K Simonyan, S Noury, N Casagrande, ...
International Conference on Machine Learning, 2410-2419, 2018
9462018
Parallel wavenet: Fast high-fidelity speech synthesis
A Oord, Y Li, I Babuschkin, K Simonyan, O Vinyals, K Kavukcuoglu, ...
International conference on machine learning, 3918-3926, 2018
9262018
Fixing data augmentation to improve adversarial robustness
SA Rebuffi, S Gowal, DA Calian, F Stimberg, O Wiles, T Mann
arXiv preprint arXiv:2103.01946, 2021
2342021
Data augmentation can improve robustness
SA Rebuffi, S Gowal, DA Calian, F Stimberg, O Wiles, TA Mann
Advances in Neural Information Processing Systems 34, 29935-29948, 2021
2172021
Improving robustness using generated data
S Gowal, SA Rebuffi, O Wiles, F Stimberg, DA Calian, TA Mann
Advances in Neural Information Processing Systems 34, 4218-4233, 2021
2092021
A fine-grained analysis on distribution shift
O Wiles, S Gowal, F Stimberg, S Alvise-Rebuffi, I Ktena, K Dvijotham, ...
arXiv preprint arXiv:2110.11328, 2021
1792021
Wavenet based low rate speech coding
WB Kleijn, FSC Lim, A Luebs, J Skoglund, F Stimberg, Q Wang, ...
2018 IEEE international conference on acoustics, speech and signal …, 2018
1652018
Defending against image corruptions through adversarial augmentations
DA Calian, F Stimberg, O Wiles, SA Rebuffi, A Gyorgy, T Mann, S Gowal
arXiv preprint arXiv:2104.01086, 2021
462021
Heiga Zen, Alex Graves, Helen King, Tom Walters, Dan Belov, and Demis Hassabis
A Van Den Oord, Y Li, I Babuschkin, K Simonyan, O Vinyals, ...
Parallel wavenet: Fast high-fidelity speech synthesis. CoRR, abs/1711.10433, 2017
322017
Bayesian inference for change points in dynamical systems with reusable states-a chinese restaurant process approach
F Stimberg, A Ruttor, M Opper
Artificial Intelligence and Statistics, 1117-1124, 2012
162012
Inference in continuous-time change-point models
F Stimberg, M Opper, G Sanguinetti, A Ruttor
Advances in Neural Information Processing Systems 24, 2011
162011
WaveNetEQ—Packet loss concealment with WaveRNN
F Stimberg, A Narest, A Bazzica, L Kolmodin, PB Gonzalez, O Sharonova, ...
2020 54th Asilomar Conference on Signals, Systems, and Computers, 672-676, 2020
122020
Poisson process jumping between an unknown number of rates: application to neural spike data
F Stimberg, A Ruttor, M Opper
Advances in Neural Information Processing Systems 27, 2014
72014
Benchmarking robustness to adversarial image obfuscations
F Stimberg, A Chakrabarti, CT Lu, H Hazimeh, O Stretcu, W Qiao, Y Liu, ...
Advances in Neural Information Processing Systems 36, 2024
42024
A fine-grained analysis of robustness to distribution shifts
O Wiles, S Gowal, F Stimberg, SA Rebuffi, I Ktena, KD Dvijotham, ...
NeurIPS 2021 Workshop on Distribution Shifts: Connecting Methods and …, 2021
22021
Doing more with less: Improving robustness using generated data
S Gowal, SA Rebuffi, O Wiles, F Stimberg, D Calian, T Mann, L DeepMind
ICLR Workshop on Security and Safety in Machine Learning Systems, 2021
22021
Flexible birth-death MCMC sampler for changepoint models
F Stimberg
PQDT-Global, 2016
12016
Documentation of the SwitchSampler Program Version 1.0
F Stimberg
2016
Comparing diffusion and weak noise approximations for inference in reaction models
A Ruttor, F Stimberg, M Opper
Machine Learning in Systems Biology, 149, 2010
2010
Comparing Markov Chain Monte Carlo Proposal Densities for Diffusion Processes
F Stimberg
Technische Universität Berlin, 2010
2010
В данный момент система не может выполнить эту операцию. Повторите попытку позднее.
Статьи 1–20