Zobrazeno 1 - 10
of 163 875
pro vyhledávání: '"Günter, A"'
Autor:
Rote, Günter
We construct a probabilistic finite automaton (PFA) with 7 states and an input alphabet of 5 symbols for which the PFA Emptiness Problem is undecidable. The only input for the decision problem is the starting distribution. For the proof, we use reduc
Externí odkaz:
http://arxiv.org/abs/2412.05198
Autor:
Bothe, Dieter, Liu, Jun, Druet, Pierre-Etienne, Maric, Tomislav, Niethammer, Matthias, Brenn, Günter
An analytical derivation of the buoyancy-induced initial acceleration of a spherical gas bubble in a host liquid is presented. The theory makes no assumptions further than applying the two-phase incompressible Navier-Stokes equations, showing that ne
Externí odkaz:
http://arxiv.org/abs/2411.10916
We propose a novel algorithm for combined unit/filter and layer pruning of deep neural networks that functions during training and without requiring a pre-trained network to apply. Our algorithm optimally trades-off learning accuracy and pruning leve
Externí odkaz:
http://arxiv.org/abs/2411.09127
The structure and function of a protein are determined by its amino acid sequence. While random mutations change a protein's sequence, evolutionary forces shape its structural fold and biological activity. Studies have shown that neutral networks can
Externí odkaz:
http://arxiv.org/abs/2411.09054
Autor:
Schmidinger, Niklas, Schneckenreiter, Lisa, Seidl, Philipp, Schimunek, Johannes, Hoedt, Pieter-Jan, Brandstetter, Johannes, Mayr, Andreas, Luukkonen, Sohvi, Hochreiter, Sepp, Klambauer, Günter
Language models for biological and chemical sequences enable crucial applications such as drug discovery, protein engineering, and precision medicine. Currently, these language models are predominantly based on Transformer architectures. While Transf
Externí odkaz:
http://arxiv.org/abs/2411.04165
Autor:
Schmied, Thomas, Adler, Thomas, Patil, Vihang, Beck, Maximilian, Pöppel, Korbinian, Brandstetter, Johannes, Klambauer, Günter, Pascanu, Razvan, Hochreiter, Sepp
In recent years, there has been a trend in the field of Reinforcement Learning (RL) towards large action models trained offline on large-scale datasets via sequence modeling. Existing models are primarily based on the Transformer architecture, which
Externí odkaz:
http://arxiv.org/abs/2410.22391
We estimate collapse rates of axion stars in our galaxy based on the axion minicluster mass function of the Milky Way dark matter halo. We consider axion-like particles with different temperature evolution of the axion mass, including the QCD axion w
Externí odkaz:
http://arxiv.org/abs/2410.13082
Autor:
Wilflingseder, Christoph, Aberl, Johannes, Navarette, Enrique Prado, Hesser, Günter, Groiss, Heiko, Liedke, Maciej O., Butterling, Maik, Wagner, Andreas, Hirschmann, Eric, Corley-Wiciak, Cedric, Zoellner, Marvin H., Capellini, Giovanni, Fromherz, Thomas, Brehm, Moritz
Germanium (Ge), the next-in-line group-IV material, bears great potential to add functionality and performance to next-generation nanoelectronics and solid-state quantum transport based on silicon (Si) technology. Here, we investigate the direct epit
Externí odkaz:
http://arxiv.org/abs/2410.03295
Axion-like particles, which we call axions, can compose the missing dark matter and may form substructures such as miniclusters and axion stars. We obtain the mass distributions of axion stars derived from their host miniclusters in our galaxy and fi
Externí odkaz:
http://arxiv.org/abs/2409.13121
Autor:
Ostapchenko, Sergey, Sigl, Guenter
A quantitative analysis of model uncertainties for calculations of the maximum depth of proton-initiated extensive air showers (EAS) has been performed. Staying within the standard physics picture and using the conventional approach to the treatment
Externí odkaz:
http://arxiv.org/abs/2409.05501