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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,786 papers · 148 categories

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48 results for Great East Japan Earthquake

Deep learning applied to coastal LULC classification post-earthquake.

problem Automatic land cover classification on coastal areas post-disaster.
method Manual tracing, simple image segmentation, image transformation using deep learning.
result Deep learning method showed over 69% accuracy for vegetation classification.

Deep neural networks predict earthquake locations with high accuracy.

problem Predicting the location of earthquakes with high precision.
method Recurrent Convolutional Neural Networks (R-CNN) model that accounts for spatio-temporal dependencies.
result Neural networks model outperforms baseline models in predicting earthquakes with ROC AUC 0.975 and PR AUC 0.0890.

Unsupervised method detects earthquakes from raw waveforms, generalizing across datasets.

problem Lack of labeled data for earthquake detection.
method Uses deep autoencoders with cross-covariance triggering at bottleneck.
result Performance comparable to supervised methods, with strong cross-dataset generalization.

A model predicts building damage locations in near real-time using intensity-based features.

problem Accurate and timely damage diagnosis of building structures after extreme events.
method Support vector machines and Bayesian optimization for probabilistic hazard intensity determination.
result The model achieves 83.1% accuracy in identifying damage locations in a reinforced concrete moment frame.

Seismic phase association is a fundamental task in seismology that pertains to linking together phase detections on different sensors that originate from a common earthquake. It is widely employed to detect earthquakes on permanent and temporary seismic networks, and underlies most seismicity catalogs produced around t…

2018-09-08abs ↗pdf ↗

The paper generalizes Thurston's earthquake map to cluster algebras of finite type.

problem Tackling Thurston's earthquake map in the context of cluster algebras of finite type.
method Introducing a cluster algebraic generalization of Thurston's earthquake map, defined by gluing exponential maps.
result Proves an analogue of the earthquake theorem for cluster algebras of finite type, showing the cluster earthquake map is a homeomorphism.

Study shows house buyers in Christchurch value earthquake risk differently based on time since 2011 quake.

problem Understanding how house buyers' perception of earthquake risk changes over time.
method Used a hedonic price model to analyze house prices in Christchurch over three periods.
result Buyers value earthquake risk differently based on the time since the 2011 Christchurch earthquake.

In this paper we study the typical speed of a generic earthquake trajectory leaving compact sets in the moduli space of the once-punctured torus. Mirzakhani showed that the earthquake flow is measurably equivalent to the horocyclic flow, which has been studied extensively. Our main result shows that the earthquake flow…

2015-06-15abs ↗pdf ↗

Deviance Voronoi residuals improve earthquake insurance risk assessment.

problem Assessing earthquake insurance risk using spatio-temporal point process models.
method Extended Voronoi residuals and created simulation-based approach.
result Proposed formula for country-wide minimum capital test.

We prove that the bijective correspondence between the space of bounded measured laminations MLb(H)ML_b(\mathbb{H}) and the universal Teichmüller space T(H)T(\mathbb{H}) given by λEλS1λ\mapsto E^λ|_{S^1} is a homeomorphism for the Fréchet topology on MLb(H)ML_b(\mathbb{H}) and the Teichmüller topology on T(H)T(\mathbb{H}), where $E^λ…

2010-06-04abs ↗pdf ↗

We give a short proof of the fact that bounded earthquakes of the unit disk induce quasisymmetric maps of the unit circle. By a similar method, we show that symmetric maps are induced by bounded earthquakes with asymptotically trivial measures.

2006-10-10abs ↗pdf ↗

Let $\cT$ be Teichmüller space of a closed surface of genus at least 2. For any point $c\in \cT$, we describe an action of the circle on $\cT\times \cT$, which limits to the earthquake flow when one of the parameters goes to a measured lamination in the Thurston boundary of $\cT$. This circle action shares some of the …

2011-06-02abs ↗pdf ↗

A machine learning surrogate model predicts earthquake-induced building responses.

problem Expensive FE model simulations for earthquake damage estimation.
method SVD-based earthquake characterization and machine learning model training.
result Deep neural network provides most accurate predictions of building responses.

New benchmark for earthquake forecasting models shows current neural point processes are not yet suitable.

problem Lack of a modern benchmark for evaluating neural point process models in earthquake forecasting.
method Curated and standardized earthquake catalog, evaluation protocols, and datasets.
result None of the tested NPPs outperformed the classical ETAS model.

The paper proves a theorem about earthquake extensions of vector fields on circles.

problem Proving a theorem about earthquake extensions of vector fields on circles.
method Using the geometry of the dual of Minkowski three-space and Half-pipe three-geometry.
result A generalization of Kerckhoff's and Gardiner's infinitesimal earthquake theorems to a broader setting.

We prove an "Earthquake Theorem" for hyperbolic metrics with geodesic boundary on a compact surfaces SS with boundary: given two hyperbolic metrics with geodesic boundary on a surface with kk boundary components, there are 2k2^k right earthquakes transforming the first in the second. An alternative formulation arises…

2006-10-13abs ↗pdf ↗

The evolution of inflation, p(t), and unemployment, UE(t), in Japan has been modeled. Both variables were represented as linear functions of the change rate of labor force, dLF/LF. These models provide an accurate description of disinflation in the 1990s and a deflationary period in the 2000s. In Japan, there exists a …

2010-02-01abs ↗pdf ↗

What are East Africa's industrial opportunities? In this article we explore this question by using the Product Space to study the productive structure of five south-east African countries: Kenya, Mozambique, Rwanda, Tanzania and Zambia. The Product Space is a network connecting products that tend to be exported by the …

2012-03-01abs ↗pdf ↗

Bayesian neural networks improve earthquake rupture prediction and uncertainty estimation.

problem Insufficient data for earthquake rupture studies.
method Used Bayesian neural networks to model earthquake rupture simulations.
result Improved F1-score of 0.8334 compared to plain NN, indicating better performance.

Let X0X_0 be a complete hyperbolic surface of infinite type that has a geodesic pants decomposition with cuff lengths bounded above. The length spectrum Teichmüller space Tls(X0)T_{ls}(X_0) consists of homotopy classes of hyperbolic metrics on X0X_0 such that the ratios of the corresponding simple closed geodesic for the hy…

2012-12-02abs ↗pdf ↗

Neural model outperforms ETAS in forecasting Central Apennines earthquakes.

problem Short-term seismicity forecasting with incomplete data.
method Extended a neural network model to the magnitude domain, using it to forecast earthquakes above a target magnitude threshold.
result Neural model outperforms ETAS at lower magnitude thresholds, due to its robustness to missing data.

JAPAN uses flow-based models to create adaptive prediction areas with better coverage guarantees.

problem Inadequate prediction areas from existing conformal prediction methods, especially for multimodal distributions.
method JAPAN employs density-based conformity scores using flow-based models to construct context-adaptive prediction areas.
result JAPAN produces more accurate and context-adaptive prediction areas compared to existing methods.

We prove two related results. The first is an ``Earthquake Theorem'' for closed hyperbolic surfaces with cone singularities where the total angle is less than ππ: any two such metrics in are connected by a unique left earthquake. The second result is that the space of ``globally hyperbolic'' AdS manifolds with ``parti…

2006-09-04abs ↗pdf ↗

Machine learning predicts seasonal precipitation for East Africa.

problem Predicting seasonal precipitation for East Africa using machine learning.
method Dimension reduction via EOFs, large-scale climate variability indices as features, interpretable ML algorithm.
result The ML approach shows significant positive skill in predicting precipitation for OND season, comparable to ECMWF forecasts.

This paper adapts Thurston's earthquake metric to Riemann surfaces with marked points.

problem Defining a norm and metric on Teichmüller spaces for surfaces of arbitrary genus.
method Adapting Thurston's earthquake norm to Riemann surfaces with marked points and using complex Legendre transforms.
result Establishes a complete analogue of Thurston's earthquake norm in the conformal setting.

The landslide flow, introduced in [5], is a smoother analog of the earthquake flow on Teichmüller space which shares some of its key properties. We show here that further properties of earthquakes apply to landslides. The landslide flow is the Hamiltonian flow of a convex function. The smooth grafting map sgrsgr taking …

2012-08-08abs ↗pdf ↗

Let S be a closed surface of genus at least 2, and consider two measured geodesic laminations that fill S. Right earthquakes along these laminations are diffeomorphisms of the Teichmüller space of S. We prove that the composition of these earthquakes has a fixed point in the Teichmüller space. Another way to state this…

2008-12-18abs ↗pdf ↗