Zobrazeno 1 - 10
of 31 962
pro vyhledávání: '"Erhard, A."'
Machine Learning (ML) is crucial in many sectors, including computer vision. However, ML models trained on sensitive data face security challenges, as they can be attacked and leak information. Privacy-Preserving Machine Learning (PPML) addresses thi
Externí odkaz:
http://arxiv.org/abs/2409.01329
In this article we show that the empirical measure of certain continuous time random walks satisfies a strong large deviation principle with respect to a topology introduced in~\cite{MV2016} by Mukherjee and Varadhan. This topology is natural in mode
Externí odkaz:
http://arxiv.org/abs/2409.01290
In this work, we establish a Trotter-Kato type theorem. More precisely, we characterize the convergence in distribution of Feller processes by examining the convergence of their generators. The main novelty lies in providing quantitative estimates in
Externí odkaz:
http://arxiv.org/abs/2408.06830
Autor:
Gille, Philippe, Neher, Erhard
We prove several results on reductive group schemes over LG-rings, e.g., existence of maximal tori and conjugacy of parabolic subgroups. These were proven in SGA3 for the special case of semilocal rings. We apply these results to establish cancellati
Externí odkaz:
http://arxiv.org/abs/2407.02021
Characteristic shock effects in silica serve as a key indicator of historical impacts at geological sites. Despite this geological significance, atomistic details of structural transformations under high pressure and shock compression remain poorly u
Externí odkaz:
http://arxiv.org/abs/2406.17676
Autor:
Aichinger, Erhard
We provide a self-contained introduction to Gr\"obner bases of submodules of $R[x_1, \ldots, x_n]^k$, where $R$ is a Euclidean domain, and explain how to use these bases to solve linear systems over $R[x_1, \ldots, x_n]$.
Comment: Survey paper
Comment: Survey paper
Externí odkaz:
http://arxiv.org/abs/2406.06994
Efficient, reliable and easy-to-use structure recognition of atomic environments is essential for the analysis of atomic scale computer simulations. In this work, we train two neuronal network (NN) architectures, namely PointNet and dynamic graph con
Externí odkaz:
http://arxiv.org/abs/2405.05156
We consider the (discrete) parabolic Anderson model $\partial u(t,x)/\partial t=\Delta u(t,x) +\xi_t(x) u(t,x)$, $t\geq 0$, $x\in \mathbb{Z}^d$. Here, the $\xi$-field is $\mathbb{R}$-valued, acting as a dynamic random environment, and $\Delta$ repres
Externí odkaz:
http://arxiv.org/abs/2403.17669
Autor:
Reschenhofer, Erhard
The results of a recent simulation with a complex global climate model suggest that the overturning component of the freshwater transport at the southern boundary of the Atlantic could be used as an early-warning indicator of an AMOC collapse. Howeve
Externí odkaz:
http://arxiv.org/abs/2402.16600
We construct a globalization of Ferrand's norm functor over rings which generalizes it to the setting of a finite locally free morphism of schemes $T\to S$ of constant rank. It sends quasi-coherent modules over $T$ to quasi-coherent modules over $S$.
Externí odkaz:
http://arxiv.org/abs/2401.15051