Zobrazeno 1 - 10
of 231
pro vyhledávání: '"Ross, Zachary"'
Regression on function spaces is typically limited to models with Gaussian process priors. We introduce the notion of universal functional regression, in which we aim to learn a prior distribution over non-Gaussian function spaces that remains mathem
Externí odkaz:
http://arxiv.org/abs/2404.02986
Autor:
Ross, Zachary E.
Accurate models of fault zone geometry are important for scientific and hazard applications. While seismicity can provide high-resolution point measurements of fault geometry, extrapolating these measurements to volumes may involve making strong assu
Externí odkaz:
http://arxiv.org/abs/2403.18982
Numerical simulations of seismic wave propagation in heterogeneous 3D media are central to investigating subsurface structures and understanding earthquake processes, yet are computationally expensive for large problems. This is particularly problema
Externí odkaz:
http://arxiv.org/abs/2311.09608
Autor:
Shi, Yaozhong, Lavrentiadis, Grigorios, Asimaki, Domniki, Ross, Zachary E., Azizzadenesheli, Kamyar
We present a data-driven framework for ground-motion synthesis that generates three-component acceleration time histories conditioned on moment magnitude, rupture distance , time-average shear-wave velocity at the top $30m$ ($V_{S30}$), and style of
Externí odkaz:
http://arxiv.org/abs/2309.03447
Autor:
Stevenson, Adam T., Haswell, Carole A., Barnes, John R., Barstow, Joanna K., Ross, Zachary O. B.
We present additional HARPS radial velocity observations of the highly eccentric ($e \sim 0.6$) binary system DMPP-3AB, which comprises a K0V primary and a low-mass companion at the hydrogen burning limit. The binary has a $507$ d orbital period and
Externí odkaz:
http://arxiv.org/abs/2305.06263
Seismic phase picking is the task of annotating seismograms with seismic wave arrival times and underpins earthquake monitoring operations globally. State-of-the-art approaches for phase picking use deep neural networks to annotate seismograms at eac
Externí odkaz:
http://arxiv.org/abs/2305.03269
Distributed Acoustic Sensing (DAS) is an emerging technology for earthquake monitoring and subsurface imaging. The recorded seismic signals by DAS have several distinct characteristics, such as unknown coupling effects, strong anthropogenic noise, an
Externí odkaz:
http://arxiv.org/abs/2302.08747
Autor:
Muir, Jack B., Ross, Zachary E.
The spatio-temporal properties of seismicity give us incisive insight into the stress state evolution and fault structures of the crust. Empirical models based on self-exciting point-processes continue to provide an important tool for analyzing seism
Externí odkaz:
http://arxiv.org/abs/2301.10518
Seismic phase association is the task of grouping phase arrival picks across a seismic network into subsets with common origins. Building on recent successes in this area with machine learning tools, we introduce a neural mixture model association al
Externí odkaz:
http://arxiv.org/abs/2301.02597
Earthquake hypocenters form the basis for a wide array of seismological analyses. Pick-based earthquake location workflows rely on the accuracy of phase pickers and may be biased when dealing with complex earthquake sequences in heterogeneous media.
Externí odkaz:
http://arxiv.org/abs/2210.06636