Statistical physics approach to understanding the multiscale dynamics of earthquake fault systems

JB Rundle, DL Turcotte, R Shcherbakov… - Reviews of …, 2003 - Wiley Online Library
Earthquakes and the faults upon which they occur interact over a wide range of spatial and
temporal scales. In addition, many aspects of regional seismicity appear to be stochastic …

Statistical physics approach to earthquake occurrence and forecasting

L de Arcangelis, C Godano, JR Grasso, E Lippiello - Physics Reports, 2016 - Elsevier
There is striking evidence that the dynamics of the Earth crust is controlled by a wide variety
of mutually dependent mechanisms acting at different spatial and temporal scales. The …

Neural network models for earthquake magnitude prediction using multiple seismicity indicators

A Panakkat, H Adeli - International journal of neural systems, 2007 - World Scientific
Neural networks are investigated for predicting the magnitude of the largest seismic event in
the following month based on the analysis of eight mathematically computed parameters …

Nowcasting earthquakes by visualizing the earthquake cycle with machine learning: A comparison of two methods

JB Rundle, A Donnellan, G Fox, JP Crutchfield - Surveys in Geophysics, 2022 - Springer
The earthquake cycle of stress accumulation and release is associated with the elastic
rebound hypothesis proposed by HF Reid following the M7. 9 San Francisco earthquake of …

Testing alarm-based earthquake predictions

JD Zechar, TH Jordan - Geophysical Journal International, 2008 - academic.oup.com
Motivated by a recent resurgence in earthquake predictability research, we present a
method for testing alarm-based earthquake predictions. The testing method is based on the …

Joint modeling of visual objects and relations for scene graph generation

M Xu, M Qu, B Ni, J Tang - Advances in Neural Information …, 2021 - proceedings.neurips.cc
An in-depth scene understanding usually requires recognizing all the objects and their
relations in an image, encoded as a scene graph. Most existing approaches for scene graph …

Seismicity-based earthquake forecasting techniques: Ten years of progress

KF Tiampo, R Shcherbakov - Tectonophysics, 2012 - Elsevier
Earthquake fault systems interact over a broad spectrum of spatial and temporal scales and,
in recent years, studies of the regional seismicity in a variety of regions have produced a …

Nowcasting earthquakes in Southern California with machine learning: Bursts, swarms, and aftershocks may be related to levels of regional tectonic stress

JB Rundle, A Donnellan - Earth and Space Science, 2020 - Wiley Online Library
Abstract Seismic bursts in Southern California are sequences of small earthquakes strongly
clustered in space and time and include seismic swarms and aftershock sequences. A …

Spatially variable model for extracting TIR anomalies before earthquakes: Application to Chinese Mainland

Y Zhang, Q Meng, G Ouillon, D Sornette, W Ma… - Remote Sensing of …, 2021 - Elsevier
There are several long-term statistical researches using the Molchan diagram (MD) to prove
the relation between thermal infrared (TIR) anomalies and earthquakes in different regions …

A RELM earthquake forecast based on pattern informatics

JR Holliday, C Chen, KF Tiampo… - Seismological …, 2007 - pubs.geoscienceworld.org
There have been a wide variety of approaches applied to forecasting earthquakes (Turcotte
1991; Kanamori 2003). These approaches can be divided into two general classes. The first …