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pro vyhledávání: '"Fabian, H"'
Understanding how the brain processes dynamic natural stimuli remains a fundamental challenge in neuroscience. Current dynamic neural encoding models either take stimuli as input but ignore shared variability in neural responses, or they model this v
Externí odkaz:
http://arxiv.org/abs/2410.16136
A high degree of structural complexity arises in dynamic neuronal dendrites due to extensive branching patterns and diverse spine morphologies, which enable the nervous system to adjust function, construct complex input pathways and thereby enhance t
Externí odkaz:
http://arxiv.org/abs/2410.09868
Autor:
Turishcheva, Polina, Fahey, Paul G., Vystrčilová, Michaela, Hansel, Laura, Froebe, Rachel, Ponder, Kayla, Qiu, Yongrong, Willeke, Konstantin F., Bashiri, Mohammad, Baikulov, Ruslan, Zhu, Yu, Ma, Lei, Yu, Shan, Huang, Tiejun, Li, Bryan M., De Wulf, Wolf, Kudryashova, Nina, Hennig, Matthias H., Rochefort, Nathalie L., Onken, Arno, Wang, Eric, Ding, Zhiwei, Tolias, Andreas S., Sinz, Fabian H., Ecker, Alexander S
Understanding how biological visual systems process information is challenging because of the nonlinear relationship between visual input and neuronal responses. Artificial neural networks allow computational neuroscientists to create predictive mode
Externí odkaz:
http://arxiv.org/abs/2407.09100
Deep predictive models of neuronal activity have recently enabled several new discoveries about the selectivity and invariance of neurons in the visual cortex. These models learn a shared set of nonlinear basis functions, which are linearly combined
Externí odkaz:
http://arxiv.org/abs/2406.12625
Single camera 3D pose estimation is an ill-defined problem due to inherent ambiguities from depth, occlusion or keypoint noise. Multi-hypothesis pose estimation accounts for this uncertainty by providing multiple 3D poses consistent with the 2D measu
Externí odkaz:
http://arxiv.org/abs/2403.06164
Publikováno v:
SciPost Phys. 17, 139 (2024)
We consider the probability distributions of the subsystem (staggered) magnetization in ordered and disordered models of quantum magnets in D dimensions. We focus on Heisenberg antiferromagnets and long-range transverse-field Ising models as particul
Externí odkaz:
http://arxiv.org/abs/2312.11333
Publikováno v:
Phys. Rev. A 109, 032208, (2024)
The presence of long-lived oscillations in the expectation values of local observables after quantum quenches has recently attracted considerable attention in relation to weak ergodicity breaking. Here we focus on an alternative mechanism that gives
Externí odkaz:
http://arxiv.org/abs/2307.04466
Autor:
Essler, Fabian H L
Publikováno v:
Physica A,127572 (2022)
These are notes based on lectures given at the 2021 summer school on Fundamental Problems in Statistical Physics XV. Their purpose is to give a very brief introduction to Generalized Hydrodynamics, which provides a description of the large scale stru
Externí odkaz:
http://arxiv.org/abs/2306.17072
Autor:
Essler, Fabian H. L., Krauth, Werner
Markov-chain Monte Carlo (MCMC), the field of stochastic algorithms built on the concept of sampling, has countless applications in science and technology. The overwhelming majority of MCMC algorithms are time-reversible and satisfy the detailed-bala
Externí odkaz:
http://arxiv.org/abs/2306.13059
Autor:
Turishcheva, Polina, Fahey, Paul G., Hansel, Laura, Froebe, Rachel, Ponder, Kayla, Vystrčilová, Michaela, Willeke, Konstantin F., Bashiri, Mohammad, Wang, Eric, Ding, Zhiwei, Tolias, Andreas S., Sinz, Fabian H., Ecker, Alexander S.
Understanding how biological visual systems process information is challenging due to the complex nonlinear relationship between neuronal responses and high-dimensional visual input. Artificial neural networks have already improved our understanding
Externí odkaz:
http://arxiv.org/abs/2305.19654