Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Romaszko, Lukasz"'
Publikováno v:
Pattern Recognition, Volume 105, 2020, 107369
We develop a Learning Direct Optimization (LiDO) method for the refinement of a latent variable model that describes input image x. Our goal is to explain a single image x with an interpretable 3D computer graphics model having scene graph latent var
Externí odkaz:
http://arxiv.org/abs/1812.07524
Autor:
Romaszko, Lukasz, Borowska, Agnieszka, Lazarus, Alan, Dalton, David, Berry, Colin, Luo, Xiaoyu, Husmeier, Dirk, Gao, Hao
Publikováno v:
In Artificial Intelligence In Medicine September 2021 119
Publikováno v:
In Pattern Recognition September 2020 105
Autor:
Goodfellow, Ian J., Erhan, Dumitru, Carrier, Pierre Luc, Courville, Aaron, Mirza, Mehdi, Hamner, Ben, Cukierski, Will, Tang, Yichuan, Thaler, David, Lee, Dong-Hyun, Zhou, Yingbo, Ramaiah, Chetan, Feng, Fangxiang, Li, Ruifan, Wang, Xiaojie, Athanasakis, Dimitris, Shawe-Taylor, John, Milakov, Maxim, Park, John, Ionescu, Radu, Popescu, Marius, Grozea, Cristian, Bergstra, James, Xie, Jingjing, Romaszko, Lukasz, Xu, Bing, Chuang, Zhang, Bengio, Yoshua
The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge. We describe the datasets created for th
Externí odkaz:
http://arxiv.org/abs/1307.0414
Autor:
Goodfellow, Ian J., Erhan, Dumitru, Luc Carrier, Pierre, Courville, Aaron, Mirza, Mehdi, Hamner, Ben, Cukierski, Will, Tang, Yichuan, Thaler, David, Lee, Dong-Hyun, Zhou, Yingbo, Ramaiah, Chetan, Feng, Fangxiang, Li, Ruifan, Wang, Xiaojie, Athanasakis, Dimitris, Shawe-Taylor, John, Milakov, Maxim, Park, John, Ionescu, Radu, Popescu, Marius, Grozea, Cristian, Bergstra, James, Xie, Jingjing, Romaszko, Lukasz, Xu, Bing, Chuang, Zhang, Bengio, Yoshua
Publikováno v:
In Neural Networks April 2015 64:59-63
Autor:
Romaszko, Lukasz
The goal of scene understanding is to interpret images, so as to infer the objects present in a scene, their poses and fine-grained details. This thesis focuses on methods that can provide a much more detailed explanation of the scene than standard b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______463::c14a6be619f2312f6c5349e7c7301236
https://hdl.handle.net/1842/37006
https://hdl.handle.net/1842/37006
Statistical emulation is a promising approach for the translation of cardio-mechanical modelling into the clinical practice. However, a key challenge is to find a low-dimensional representation of the heart, or, for the specific purpose of diagnosing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8ec3035050d4c097b3f2826bb64fd41
https://eprints.gla.ac.uk/193802/1/193802.pdf
https://eprints.gla.ac.uk/193802/1/193802.pdf
Publikováno v:
Proceedings of the International Conference on Statistics: Theory and Applications.
Biomechanical studies of the left ventricle (LV) typically rely on a mesh of finite element nodes for a discrete representation of the LV geometry, which is used in an approximate numerical solution of the cardio-mechanical equations based on finite-
Autor:
Guyon, Isabelle, Chaabane, Imad, Escalante, Hugo Jair, Escalera, Sergio, Jajetic, Damir, Lloyd, James Robert, Macia, Nuria, Ray, Bisakha, Romaszko, Lukasz, Sebag, Michèle, Statnikov, Alexander, Treguer, Sebastien, Viegas, Evelyne
Publikováno v:
JMLR: Workshop and Conference Proceedings
International Conference in Machine Learning (ICML 2016) Workshops
International Conference in Machine Learning (ICML 2016) Workshops, 2016, New-York, United States. pp.1-8
International Conference in Machine Learning (ICML 2016) Workshops
International Conference in Machine Learning (ICML 2016) Workshops, 2016, New-York, United States. pp.1-8
International audience; The ChaLearn AutoML Challenge team conducted a large scale evaluation of fully auto-matic, black-box learning machines for feature-based classi cation and regression problems. The test bed was composed of 30 data sets from a w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::9940b5885d9c3562e784c0d2ba8bebf2
https://hal.archives-ouvertes.fr/hal-01381145
https://hal.archives-ouvertes.fr/hal-01381145
Autor:
Inel, Oana, Khamkham, Khalid, Cristea, Tatiana, Dumitrache, Anca, Rutjes, Arne, van der Ploeg, Jelle, Romaszko, Lukasz, Aroyo, Lora, Sips, Robert-Jan
Publikováno v:
Semantic Web - ISWC 2014: 13th International Semantic Web Conference, Riva del Garda, Italy, October 19-23, 2014. Proceedings, Part II; 2014, p486-504, 19p