Zobrazeno 1 - 10
of 1 794
pro vyhledávání: '"Boffi, P."'
Diffusion-based generative models provide a powerful framework for learning to sample from a complex target distribution. The remarkable empirical success of these models applied to high-dimensional signals, including images and video, stands in star
Externí odkaz:
http://arxiv.org/abs/2410.11275
The Special Theory of Relativity, introduced by Albert Einstein in the early 20th century, marked a radical shift in our understanding of space and time. Nevertheless, the theory's non-intuitive implications continue to pose conceptual challenges for
Externí odkaz:
http://arxiv.org/abs/2408.01442
A posteriori error estimator is derived for an elliptic interface problem in the fictitious domain formulation with distributed Lagrange multiplier considering a discontinuous Lagrange multiplier finite element space. A posteriori error estimation pl
Externí odkaz:
http://arxiv.org/abs/2407.00786
Generative models based on dynamical transport of measure, such as diffusion models, flow matching models, and stochastic interpolants, learn an ordinary or stochastic differential equation whose trajectories push initial conditions from a known base
Externí odkaz:
http://arxiv.org/abs/2406.07507
We consider a fictitious domain formulation for fluid-structure interaction problems based on a distributed Lagrange multiplier to couple the fluid and solid behaviors. How to deal with the coupling term is crucial since the construction of the assoc
Externí odkaz:
http://arxiv.org/abs/2406.03981
Autor:
Chen, Yifan, Goldstein, Mark, Hua, Mengjian, Albergo, Michael S., Boffi, Nicholas M., Vanden-Eijnden, Eric
We propose a framework for probabilistic forecasting of dynamical systems based on generative modeling. Given observations of the system state over time, we formulate the forecasting problem as sampling from the conditional distribution of the future
Externí odkaz:
http://arxiv.org/abs/2403.13724
This paper focuses on the numerical solution of elliptic partial differential equations (PDEs) with Dirichlet and mixed boundary conditions, specifically addressing the challenges arising from irregular domains. Both finite element method (FEM) and f
Externí odkaz:
http://arxiv.org/abs/2402.04048
Autor:
Ma, Nanye, Goldstein, Mark, Albergo, Michael S., Boffi, Nicholas M., Vanden-Eijnden, Eric, Xie, Saining
We present Scalable Interpolant Transformers (SiT), a family of generative models built on the backbone of Diffusion Transformers (DiT). The interpolant framework, which allows for connecting two distributions in a more flexible way than standard dif
Externí odkaz:
http://arxiv.org/abs/2401.08740
In this paper we introduce an abstract setting for the convergence analysis of the virtual element approximation of an acoustic vibration problem. We discuss the effect of the stabilization parameters and remark that in some cases it is possible to a
Externí odkaz:
http://arxiv.org/abs/2401.04485
Autor:
Tamimi, Amr, Caldarola, Martin, Hambura, Sebastian, Boffi, Juan C., Noordzij, Niels, Los, Johannes W. N., Guardiani, Antonio, Kooiman, Hugo, Wang, Ling, Kieser, Christian, Braun, Florian, Fognini, Andreas, Prevedel, Robert
Two-photon microscopy (2PM) has become an important tool in biology to study the structure and function of intact tissues in-vivo. However, adult mammalian tissues such as the mouse brain are highly scattering, thereby putting fundamental limits on t
Externí odkaz:
http://arxiv.org/abs/2312.14042