Zobrazeno 1 - 10
of 1 964
pro vyhledávání: '"A Ksiaźek"'
Autor:
Krukowski, Patryk, Bielawska, Anna, Książek, Kamil, Wawrzyński, Paweł, Batorski, Paweł, Spurek, Przemysław
Recently, a new Continual Learning (CL) paradigm was presented to control catastrophic forgetting, called Interval Continual Learning (InterContiNet), which relies on enforcing interval constraints on the neural network parameter space. Unfortunately
Externí odkaz:
http://arxiv.org/abs/2405.15444
Autor:
Książek, Kamil, Spurek, Przemysław
Artificial neural networks suffer from catastrophic forgetting when they are sequentially trained on multiple tasks. Many continual learning (CL) strategies are trying to overcome this problem. One of the most effective is the hypernetwork-based appr
Externí odkaz:
http://arxiv.org/abs/2310.00113
Autor:
Ignatov, Andrey, Malivenko, Grigory, Timofte, Radu, Treszczotko, Lukasz, Chang, Xin, Ksiazek, Piotr, Lopuszynski, Michal, Pioro, Maciej, Rudnicki, Rafal, Smyl, Maciej, Ma, Yujie, Li, Zhenyu, Chen, Zehui, Xu, Jialei, Liu, Xianming, Jiang, Junjun, Shi, XueChao, Xu, Difan, Li, Yanan, Wang, Xiaotao, Lei, Lei, Zhang, Ziyu, Wang, Yicheng, Huang, Zilong, Luo, Guozhong, Yu, Gang, Fu, Bin, Li, Jiaqi, Wang, Yiran, Huang, Zihao, Cao, Zhiguo, Conde, Marcos V., Sapozhnikov, Denis, Lee, Byeong Hyun, Park, Dongwon, Hong, Seongmin, Lee, Joonhee, Lee, Seunggyu, Chun, Se Young
Various depth estimation models are now widely used on many mobile and IoT devices for image segmentation, bokeh effect rendering, object tracking and many other mobile tasks. Thus, it is very crucial to have efficient and accurate depth estimation m
Externí odkaz:
http://arxiv.org/abs/2211.04470
Autor:
Bruzda, G., Polkowski, W., Nowak, R., Polkowska, A., Lech, S., Karczewski, K., Książek, M., Giuranno, D
Publikováno v:
Journal of Materials Science (2022)
Boron-doped molybdenum silicides have been already recognized as attractive candidates for space and ground ultra-high temperature applications far beyond limits of state-of-the-art nickel based superalloys. In this work, we are exploring a new metho
Externí odkaz:
http://arxiv.org/abs/2206.09464
Autor:
Szopińska, Małgorzata, Artichowicz, Wojciech, Szumińska, Danuta, Kasprowicz, Daniel, Polkowska, Żaneta, Fudala-Ksiazek, Sylwia, Luczkiewicz, Aneta
Publikováno v:
In Science of the Total Environment 15 October 2024 947
Autor:
Matuszewska, Julia, Krawiec, Adrianna, Radziemski, Artur, Uruski, Paweł, Tykarski, Andrzej, Mikuła-Pietrasik, Justyna, Książek, Krzysztof
Publikováno v:
In European Journal of Cell Biology September 2024 103(3)
Autor:
Książek, Kamil, Głomb, Przemysław, Romaszewski, Michał, Cholewa, Michał, Grabowski, Bartosz, Búza, Krisztián
Neural networks, in particular autoencoders, are one of the most promising solutions for unmixing hyperspectral data, i.e. reconstructing the spectra of observed substances (endmembers) and their relative mixing fractions (abundances), which is neede
Externí odkaz:
http://arxiv.org/abs/2109.13748
Autor:
Dettlaff, Anna, Szopińska, Małgorzata, Houghton, Daniel, Prasuła, Piotr, Han, Yisong, Walker, Marc, West, Geoff, Kamieńska-Duda, Agata, Fudala-Książek, Sylwia, Sobaszek, Michał
Publikováno v:
In Chemical Engineering Journal 1 August 2024 493
Autor:
Radomska, Dominika, Szewczyk-Roszczenko, Olga Klaudia, Marciniec, Krzysztof, Książek, Maria, Kusz, Joachim, Roszczenko, Piotr, Szymanowska, Anna, Radomski, Dominik, Bielawski, Krzysztof, Czarnomysy, Robert
Publikováno v:
In Bioorganic Chemistry July 2024 148
Autor:
Campbell, Kendrick, Vetter, Joel, Vilson, Fernandino L., Ogawa, Shellee, Baas, Wesley, Klim, Aleksandra, Paradis, Alethea, Ksiazek, Deborah, Wolff, Diana, Lai, Henry, Murphy, Gregory
Publikováno v:
In Urology June 2024 188:144-149