Zobrazeno 1 - 10
of 1 282
pro vyhledávání: '"Borș A"'
Autor:
Figgener, Jan, Bors, Jakob, Kuipers, Matthias, Hildenbrand, Felix, Junker, Mark, Koltermann, Lucas, Woerner, Philipp, Mennekes, Marc, Haberschusz, David, Kairies, Kai-Philipp, Sauer, Dirk Uwe
A battery's open circuit voltage (OCV) curve can be seen as its electrochemical signature. Its shape and age-related shift provide information on aging processes and material composition on both electrodes. However, most OCV analyses have to be condu
Externí odkaz:
http://arxiv.org/abs/2411.08025
Autor:
Bors, Dorota, Stańczy, Robert
The existence of solutions to Tolman-Openheimer-Volkoff equation with linear equation of state modeling relativistic cloud of interacting particles is proved for mass parameter below certain threshold. For the intermediate values of mass parameters m
Externí odkaz:
http://arxiv.org/abs/2408.09751
Deeper Vision Transformers (ViTs) are more challenging to train. We expose a degradation problem in deeper layers of ViT when using masked image modeling (MIM) for pre-training. To ease the training of deeper ViTs, we introduce a self-supervised lear
Externí odkaz:
http://arxiv.org/abs/2309.14136
We show that the transition function of the cascaded connection of two FSRs can be viewed as a wreath product element. This allows us to study periods of cascaded connections with algebraic methods, obtaining both a general, nontrivial upper bound on
Externí odkaz:
http://arxiv.org/abs/2309.10265
The functional graph of a function $g:X\rightarrow X$ is the directed graph with vertex set $X$ the edges of which are of the form $x\rightarrow g(x)$ for $x\in X$. Functional graphs are heavily studied because they allow one to understand the behavi
Externí odkaz:
http://arxiv.org/abs/2304.00181
Autor:
Huang, Guoxi, Bors, Adrian G.
Static appearance of video may impede the ability of a deep neural network to learn motion-relevant features in video action recognition. In this paper, we introduce a new concept, Dynamic Appearance (DA), summarizing the appearance information relat
Externí odkaz:
http://arxiv.org/abs/2211.12748
Autor:
Ye, Fei, Bors, Adrian G.
Learning from non-stationary data streams, also called Task-Free Continual Learning (TFCL) remains challenging due to the absence of explicit task information. Although recently some methods have been proposed for TFCL, they lack theoretical guarante
Externí odkaz:
http://arxiv.org/abs/2210.06579
Autor:
Ye, Fei, Bors, Adrian G.
Due to their inference, data representation and reconstruction properties, Variational Autoencoders (VAE) have been successfully used in continual learning classification tasks. However, their ability to generate images with specifications correspond
Externí odkaz:
http://arxiv.org/abs/2207.10131
Autor:
Bors, Alexander, Wang, Qiang
We determine the permutation groups $P_{\mathrm{comp}}(\mathbb{F}_q),P_{\mathrm{orth}}(\mathbb{F}_q)\leq\operatorname{Sym}(\mathbb{F}_q)$ generated by the complete mappings, respectively the orthomorphisms, of the finite field $\mathbb{F}_q$ -- both
Externí odkaz:
http://arxiv.org/abs/2207.09642
Autor:
Ye, Fei, Bors, Adrian G.
Recently, continual learning (CL) has gained significant interest because it enables deep learning models to acquire new knowledge without forgetting previously learnt information. However, most existing works require knowing the task identities and
Externí odkaz:
http://arxiv.org/abs/2207.05080