Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Kerekes, Anna"'
Autor:
Reizinger, Patrik, Ujváry, Szilvia, Mészáros, Anna, Kerekes, Anna, Brendel, Wieland, Huszár, Ferenc
The last decade has seen blossoming research in deep learning theory attempting to answer, "Why does deep learning generalize?" A powerful shift in perspective precipitated this progress: the study of overparametrized models in the interpolation regi
Externí odkaz:
http://arxiv.org/abs/2405.01964
Denoising diffusion models are a class of generative models which have recently achieved state-of-the-art results across many domains. Gradual noise is added to the data using a diffusion process, which transforms the data distribution into a Gaussia
Externí odkaz:
http://arxiv.org/abs/2305.09605
Sharpness-aware minimization (SAM) aims to improve the generalisation of gradient-based learning by seeking out flat minima. In this work, we establish connections between SAM and Mean-Field Variational Inference (MFVI) of neural network parameters.
Externí odkaz:
http://arxiv.org/abs/2210.10452
In gradient descent, changing how we parametrize the model can lead to drastically different optimization trajectories, giving rise to a surprising range of meaningful inductive biases: identifying sparse classifiers or reconstructing low-rank matric
Externí odkaz:
http://arxiv.org/abs/2111.11542
Publikováno v:
REVISTA RISCURI SI CATASTROFE / Risks and Catastrophes Journal. 30(1):57-65
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=1075506
Denoising diffusion models are a class of generative models which have recently achieved state-of-the-art results across many domains. Gradual noise is added to the data using a diffusion process, which transforms the data distribution into a Gaussia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c9955041ccbcd9567d54696b2812da0
http://arxiv.org/abs/2305.09605
http://arxiv.org/abs/2305.09605
Publikováno v:
Revista de Geomorfologie. 2020, Vol. 22, p43-59. 17p.
Autor:
KEREKES, Anna-Hajnalka1 annakrks@yahoo.com, ALEXE, Mircea2 mircea.alexe@ubbcluj.ro
Publikováno v:
Annals of the University of Oradea, Geography Series / Analele Universitatii din Oradea, Seria Geografie. Dec2019, Vol. 29 Issue 2, p52-63. 12p.
Publikováno v:
Revista de Geomorfologie. 2018, Vol. 20, p130-146. 17p.
Autor:
Kerekes Anna-Hajnalka
Publikováno v:
Geographia Napocensis, Vol XII, Iss 1, Pp 57-70 (2018)
Road Network Analysis Using GIS Techniques in the Interest of Finding the Optimal Routes for Emergency Situations.Case Study: Cluj-Napoca (Romania) - The city of Cluj-Napoca, the second largest city in Romania, is characterized by a rapid, dynamic sp