Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Lucas Theis"'
Autor:
Philipp Berens, Jeremy Freeman, Thomas Deneux, Nikolay Chenkov, Thomas McColgan, Artur Speiser, Jakob H Macke, Srinivas C Turaga, Patrick Mineault, Peter Rupprecht, Stephan Gerhard, Rainer W Friedrich, Johannes Friedrich, Liam Paninski, Marius Pachitariu, Kenneth D Harris, Ben Bolte, Timothy A Machado, Dario Ringach, Jasmine Stone, Luke E Rogerson, Nicolas J Sofroniew, Jacob Reimer, Emmanouil Froudarakis, Thomas Euler, Miroslav Román Rosón, Lucas Theis, Andreas S Tolias, Matthias Bethge
Publikováno v:
PLoS Computational Biology, Vol 14, Iss 5, p e1006157 (2018)
In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to
Externí odkaz:
https://doaj.org/article/358eea9214b64f3889ddd1a4b6f1cd9d
Publikováno v:
PLoS Computational Biology, Vol 9, Iss 11, p e1003356 (2013)
Generalized linear models (GLMs) represent a popular choice for the probabilistic characterization of neural spike responses. While GLMs are attractive for their computational tractability, they also impose strong assumptions and thus only allow for
Externí odkaz:
https://doaj.org/article/24ded4c8239945e2b32360eaaa6eaf7b
Publikováno v:
PLoS ONE, Vol 7, Iss 7, p e39857 (2012)
We present a probabilistic model for natural images that is based on mixtures of Gaussian scale mixtures and a simple multiscale representation. We show that it is able to generate images with interesting higher-order correlations when trained on nat
Externí odkaz:
https://doaj.org/article/86e2ed5c3d2b473f89b16a52e3d7d0b7
The goal of data compression is to reduce the number of bits needed to represent useful information. Neural, or learned compression, is the application of neural networks and related machine learning techniques to this task. This monograph aims to se
Publikováno v:
Nguyen Phuoc, T, Li, C, Theis, L, Richardt, C & Yang, Y 2020, HoloGAN: Unsupervised Learning of 3D Representations From Natural Images . in 2019 IEEE/CVF International Conference on Computer Vision (ICCV) ., 9010343, 2019 IEEE/CVF International Conference on Computer Vision (ICCV), IEEE, pp. 7588-7597, International Conference on Computer Vision 2019, 27/10/19 . https://doi.org/10.1109/ICCV.2019.00768
2019 IEEE/CVF International Conference on Computer Vision (ICCV)
ICCV Workshops
2019 IEEE/CVF International Conference on Computer Vision (ICCV)
ICCV Workshops
We propose a novel generative adversarial network (GAN) for the task of unsupervised learning of 3D representations from natural images. Most generative models rely on 2D kernels to generate images and make few assumptions about the 3D world. These m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1565a335c6f0b5fb8fcc4b3190c74a24
https://purehost.bath.ac.uk/ws/files/216883001/holoGAN_iccv19.pdf
https://purehost.bath.ac.uk/ws/files/216883001/holoGAN_iccv19.pdf
Publikováno v:
A Natureza e o Conceito do Direito
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb9e12730cccee8de55df92a104a648c
https://doi.org/10.22533/at.ed.76819081011
https://doi.org/10.22533/at.ed.76819081011
Autor:
Wenzhe Shi, Pranay Kumar Myana, Lucas Theis, Ferenc Huszar, Deepak Dilipkumar, Sofia Ira Ktena, Steven Yoo, Alykhan Tejani
Publikováno v:
RecSys
One of the challenges in display advertising is that the distribution of features and click through rate (CTR) can exhibit large shifts over time due to seasonality, changes to ad campaigns and other factors. The predominant strategy to keep up with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee39e89b70ec1d3dfa166b4ba4c94068
https://doi.org/10.1145/3298689.3347002
https://doi.org/10.1145/3298689.3347002
Publikováno v:
Computational Statistics Data Analysis
We study modeling and inference with the Elliptical Gamma Distribution (EGD). We consider maximum likelihood (ML) estimation for EGD scatter matrices, a task for which we develop new fixed-point algorithms. Our algorithms are efficient and converge t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e993f453646adb855b13d9e7600c02c8
https://doi.org/10.1016/j.csda.2016.02.009
https://doi.org/10.1016/j.csda.2016.02.009
Publikováno v:
PCS
To effectively evaluate subjective visual quality in weakly-controlled environments, we propose an Adaptive Paired Comparison method based on particle filtering. As our approach requires each sample to be rated only once, the test time compared to re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53df80ecaa95b746a11b94a08313229e