Zobrazeno 1 - 10
of 962
pro vyhledávání: '"Ni, Hao"'
On a compact Riemannian manifold $M,$ we show that the Riemannian distance function $d(x,y)$ can be explicitly reconstructed from suitable asymptotics of the expected signature of Brownian bridge from $x$ to $y$. In addition, by looking into the asym
Externí odkaz:
http://arxiv.org/abs/2407.13086
Keypoint data has received a considerable amount of attention in machine learning for tasks like action detection and recognition. However, human experts in movement such as doctors, physiotherapists, sports scientists and coaches use a notion of joi
Externí odkaz:
http://arxiv.org/abs/2406.17443
Background: Nanoparticles can accumulate in solid tumors, serving as diagnostic or therapeutic agents for cancer. Clinical translation is challenging due to low accumulation in tumors and heterogeneity between tumor types and individuals. Tools to id
Externí odkaz:
http://arxiv.org/abs/2406.10146
Generative adversarial networks (GANs) have emerged as a powerful tool for generating high-fidelity data. However, the main bottleneck of existing approaches is the lack of supervision on the generator training, which often results in undamped oscill
Externí odkaz:
http://arxiv.org/abs/2405.17191
Since the weak convergence for stochastic processes does not account for the growth of information over time which is represented by the underlying filtration, a slightly erroneous stochastic model in weak topology may cause huge loss in multi-period
Externí odkaz:
http://arxiv.org/abs/2405.14913
A central question in rough path theory is characterising the law of stochastic processes. It is established in [I. Chevyrev $\&$ T. Lyons, Characteristic functions of measures on geometric rough paths, $\textit{Ann. Probab.}$ $\textbf{44}$ (2016), 4
Externí odkaz:
http://arxiv.org/abs/2404.18661
Skeleton-based action recognition (SAR) in videos is an important but challenging task in computer vision. The recent state-of-the-art (SOTA) models for SAR are primarily based on graph convolutional neural networks (GCNs), which are powerful in extr
Externí odkaz:
http://arxiv.org/abs/2403.15212
The signature of a path, as a fundamental object in Rough path theory, serves as a generating function for non-commutative monomials on path space. It transforms the path into a grouplike element in the tensor algebra space, summarising the path fait
Externí odkaz:
http://arxiv.org/abs/2401.02393
Domain generalization person re-identification (DG-ReID) aims to train a model on source domains and generalize well on unseen domains. Vision Transformer usually yields better generalization ability than common CNN networks under distribution shifts
Externí odkaz:
http://arxiv.org/abs/2308.03322
It is well known that, when numerically simulating solutions to SDEs, achieving a strong convergence rate better than O(\sqrt{h}) (where h is the step size) requires the use of certain iterated integrals of Brownian motion, commonly referred to as it
Externí odkaz:
http://arxiv.org/abs/2308.02452