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Mikołaj Bińkowski
Mikołaj Bińkowski
Research Scientist, DeepMind
Verified email at google.com
Title
Cited by
Cited by
Year
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
15252022
Demystifying MMD GANs
M Bińkowski, DJ Sutherland, M Arbel, A Gretton
6th International Conference on Learning Representations, 2018
11452018
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
2302021
End-to-end adversarial text-to-speech
J Donahue, S Dieleman, M Bińkowski, E Elsen, K Simonyan
arXiv preprint arXiv:2006.03575, 2020
1962020
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
1752017
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
1372021
On gradient regularizers for MMD GANs
M Arbel, DJ Sutherland, M Bińkowski, A Gretton
Advances in neural information processing systems 31, 2018
992018
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
972019
Step-unrolled denoising autoencoders for text generation
N Savinov, J Chung, M Binkowski, E Elsen, A Oord
arXiv preprint arXiv:2112.06749, 2021
642021
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
21
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
17
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
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
5
Flamingo: a visual language model for few-shot learning. CoRR, abs/2204.14198, 2022. doi: 10.48550
JB Alayrac, J Donahue, P Luc, A Miech, I Barr, Y Hasson, K Lenc, ...
arXiv preprint arXiv.2204.14198, 0
5
Endogeneous dynamics of intraday liquidity
M Bińkowski, CA Lehalle
arXiv preprint arXiv:1811.03766, 2018
4*2018
A Deep Learning Approach for Characterizing Major Galaxy Mergers
S Koppula, V Bapst, M Huertas-Company, S Blackwell, ...
arXiv preprint arXiv:2102.05182, 2021
32021
Adversarial Text-to-Speech for low-resource languages
A Elneima, M Bińkowski
Proceedings of the The Seventh Arabic Natural Language Processing Workshop …, 2022
12022
Unsupervised one-to-many image translation
S Lavoie-Marchildon, S Lachapelle, M Bińkowski, A Courville, Y Bengio, ...
12018
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
2021
Training and evaluating adversarial networks: from kernel discrepancies to applications
M Binkowski
Imperial College London, 2020
2020
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