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Mikołaj Bińkowski
Mikołaj Bińkowski
Research Scientist, DeepMind
Bestätigte E-Mail-Adresse bei google.com
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Zitiert von
Zitiert von
Jahr
Flamingo: a visual language model for few-shot learning
JB Alayrac, J Donahue, P Luc, A Miech, I Barr, Y Hasson, K Lenc, ...
Advances in neural information processing systems 35, 23716-23736, 2022
37192022
Demystifying MMD GANs
M Bińkowski, DJ Sutherland, M Arbel, A Gretton
6th International Conference on Learning Representations, 2018
17072018
High fidelity speech synthesis with adversarial networks
M Bińkowski, J Donahue, S Dieleman, A Clark, E Elsen, N Casagrande, ...
8th International Conference on Learning Representations, 2019
3062019
End-to-end adversarial text-to-speech
J Donahue, S Dieleman, M Bińkowski, E Elsen, K Simonyan
arXiv preprint arXiv:2006.03575, 2020
2292020
Autoregressive convolutional neural networks for asynchronous time series
M Bińkowski, G Marti, P Donnat
Proceedings of the 35th International Conference on Machine Learning 80, 580-589, 2017
2102017
A review of two decades of correlations, hierarchies, networks and clustering in financial markets
G Marti, F Nielsen, M Bińkowski, P Donnat
Progress in information geometry: Theory and applications, 245-274, 2021
1802021
On gradient regularizers for MMD GANs
M Arbel, DJ Sutherland, M Bińkowski, A Gretton
Advances in neural information processing systems 31, 2018
1072018
Step-unrolled denoising autoencoders for text generation
N Savinov, J Chung, M Binkowski, E Elsen, A Oord
arXiv preprint arXiv:2112.06749, 2021
962021
Flamingo: a visual language model for few-shot learning, 2022
JB Alayrac, J Donahue, P Luc, A Miech, I Barr, Y Hasson, K Lenc, ...
URL https://arxiv. org/abs/2204.14198, 0
44
Demystifying mmd gans. arXiv 2018
M Binkowski, DJ Sutherland, M Arbel, A Gretton
arXiv preprint arXiv:1801.01401, 1801
291801
Flamingo: A visual language model for few-shot learning. arXiv 2022
JB Alayrac, J Donahue, P Luc, A Miech, I Barr, Y Hasson, K Lenc, ...
arXiv preprint arXiv:2204.14198, 0
29
Batch Weight for Domain Adaptation With Mass Shift
M Bińkowski, RD Hjelm, A Courville
The IEEE International Conference on Computer Vision (ICCV), 1844-1853, 2019
112019
Demystifying MMD GANs (2018)
M Binkowski, DJ Sutherland, M Arbel, A Gretton
arXiv preprint arXiv:1801.01401, 1801
111801
Flamingo: a visual language model for few-shot learning. arXiv preprint. 2022
JB Alayrac, J Donahue, P Luc, A Miech, I Barr, Y Hasson, K Lenc, ...
Source:〈 https://arxiv. org/abs/2204.14198, 0
7
High fidelity speech synthesis with adversarial networks. arXiv 2019
M Binkowski, J Donahue, S Dieleman, A Clark, E Elsen, N Casagrande, ...
arXiv preprint arXiv:1909.11646, 0
7
Adversarial Text-to-Speech for low-resource languages
A Elneima, M Bińkowski
Proceedings of the Seventh Arabic Natural Language Processing Workshop …, 2022
62022
Endogenous Dynamics of Intraday Liquidity.
M Bińkowski, CA Lehalle
Journal of Portfolio Management 48 (6), 2022
5*2022
High fidelity speech synthesis with adversarial networks
M Binkowski, K Simonyan, J Donahue, A Clark, SEL Dieleman, EK Elsen, ...
US Patent App. 17/032,578, 2021
52021
Oord, A. vd 2021. Step-unrolled denoising autoencoders for text generation
N Savinov, J Chung, M Binkowski, E Elsen
arXiv preprint arXiv:2112.06749, 0
5
Generating audio data using unaligned text inputs with an adversarial network
J Donahue, K Simonyan, SEL Dieleman, M Binkowski, EK Elsen
US Patent App. 17/339,834, 2021
32021
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