Zobrazeno 1 - 10
of 294
pro vyhledávání: '"A. TEMPCZYK"'
Local intrinsic dimension (LID) estimation methods have received a lot of attention in recent years thanks to the progress in deep neural networks and generative modeling. In opposition to old non-parametric methods, new methods use generative models
Externí odkaz:
http://arxiv.org/abs/2406.17125
We present Polite Teacher, a simple yet effective method for the task of semi-supervised instance segmentation. The proposed architecture relies on the Teacher-Student mutual learning framework. To filter out noisy pseudo-labels, we use confidence th
Externí odkaz:
http://arxiv.org/abs/2211.03850
One of the most popular estimation methods in Bayesian neural networks (BNN) is mean-field variational inference (MFVI). In this work, we show that neural networks with ReLU activation function induce posteriors, that are hard to fit with MFVI. We pr
Externí odkaz:
http://arxiv.org/abs/2207.13167
Autor:
Tempczyk, Piotr, Michaluk, Rafał, Garncarek, Łukasz, Spurek, Przemysław, Tabor, Jacek, Goliński, Adam
Most of the existing methods for estimating the local intrinsic dimension of a data distribution do not scale well to high-dimensional data. Many of them rely on a non-parametric nearest neighbors approach which suffers from the curse of dimensionali
Externí odkaz:
http://arxiv.org/abs/2206.14882
Publikováno v:
IEEE Access, Vol 12, Pp 37744-37756 (2024)
We present Polite Teacher, a simple yet effective method for the task of semi-supervised instance segmentation. The proposed architecture relies on the Teacher-Student mutual learning framework. To filter out noisy pseudo-labels, we use confidence th
Externí odkaz:
https://doaj.org/article/ff98e480ba254c1a98e6cc80df0dc061
Autor:
Wei, Xiaoxi, Faisal, A. Aldo, Grosse-Wentrup, Moritz, Gramfort, Alexandre, Chevallier, Sylvain, Jayaram, Vinay, Jeunet, Camille, Bakas, Stylianos, Ludwig, Siegfried, Barmpas, Konstantinos, Bahri, Mehdi, Panagakis, Yannis, Laskaris, Nikolaos, Adamos, Dimitrios A., Zafeiriou, Stefanos, Duong, William C., Gordon, Stephen M., Lawhern, Vernon J., Śliwowski, Maciej, Rouanne, Vincent, Tempczyk, Piotr
Transfer learning and meta-learning offer some of the most promising avenues to unlock the scalability of healthcare and consumer technologies driven by biosignal data. This is because current methods cannot generalise well across human subjects' dat
Externí odkaz:
http://arxiv.org/abs/2202.12950
n-CPS: Generalising Cross Pseudo Supervision to n Networks for Semi-Supervised Semantic Segmentation
We present n-CPS - a generalisation of the recent state-of-the-art cross pseudo supervision (CPS) approach for the task of semi-supervised semantic segmentation. In n-CPS, there are n simultaneously trained subnetworks that learn from each other thro
Externí odkaz:
http://arxiv.org/abs/2112.07528
Autor:
Żaneta Tempczyk-Nagórka
Publikováno v:
Seminare, Vol 38, Iss 3 (2022)
Coraz więcej rodzin i wychowujących się w nich dzieci jest zagrożonych wykluczeniem utrudniającym im rozwój i pełną partycypację w życiu społecznym. Jedną ze skutecznych form przeciwdziałania przyczynom i skutkom wykluczenia jest szeroka
Externí odkaz:
https://doaj.org/article/e39f490c7fb3467da670ff366f16c172
Akademický článek
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Publikováno v:
Childhood Care & Education / Problemy Opiekuńczo-Wychowawcze; 2024, Vol. 629 Issue 4, p3-16, 14p