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.
The paper analyzes tech specialization and diversification at various scales.
Unified theory explains housing cycle across metros, showing credit expansion impacts.
Study shows credit expansion in mortgage markets influenced U.S. business cycle.
In this paper, we take a new approach for time of arrival geo-localization. We show that the main sources of error in metropolitan areas are due to environmental imperfections that bias our solutions, and that we can rely on a probabilistic model to learn and compensate for them. The resulting localization error is val…
This paper explores integration and contagion among US metropolitan housing markets. The analysis applies Federal Housing Finance Agency (FHFA) house price repeat sales indexes from 384 metropolitan areas to estimate a multi-factor model of U.S. housing market integration. It then identifies statistical jumps in metrop…
Method estimates travel times on urban roads using Uber data.
Geographic diversification is fundamental to risk mitigation among investors and insurers of housing, mortgages, and mortgage-related derivatives. To characterize diversification potential, we provide estimates of integration, spatial correlation, and contagion among US metropolitan housing markets. Results reveal a hi…
A new framework reduces traffic congestion by 36%.
Random forests and LASSO methods improve small area estimation using auxiliary data.
Graph embeddings from commute networks identify socioeconomic disparities in urban areas.
Estimating the capabilities, or inputs of production, that drive and constrain the economic development of urban areas has remained a challenging goal. We posit that capabilities are instantiated in the complexity and sophistication of urban activities, the knowhow of individual workers, and the city-wide collective kn…
Bayesian calibration improves ABMs for predicting travel patterns.
We describe two recently proposed machine learning approaches for discovering emerging trends in fatal accidental drug overdoses. The Gaussian Process Subset Scan enables early detection of emerging patterns in spatio-temporal data, accounting for both the non-iid nature of the data and the fact that detecting subtle p…
Urban transformations within large and growing metropolitan areas often generate critical dynamics affecting social interactions, transport connectivity and income flow distribution. We develop a statistical-mechanical model of urban transformations, exemplified for Greater Sydney, and derive a thermodynamic descriptio…
We describe an agent-based simulation of a fictional (but feasible) information trading business. The Gas Price Information Trader (GPIT) buys information about real-time gas prices in a metropolitan area from drivers and resells the information to drivers who need to refuel their vehicles. Our simulation uses real wor…
Understanding how housing values evolve over time is important to policy makers, consumers and real estate professionals. Existing methods for constructing housing indices are computed at a coarse spatial granularity, such as metropolitan regions, which can mask or distort price dynamics apparent in local markets, such…
Understanding cities is central to addressing major global challenges from climate and health to economic resilience. Although increasingly perceived as fundamental socio-economic units, the detailed fabric of urban economic activities is only now accessible to comprehensive analyses with the availability of large data…
Study uses open data to improve traffic emissions estimation.
The paper develops a deep neural network estimator for weakly dependent processes with various loss functions.
The automatic classification of applications and services is an invaluable feature for new generation mobile networks. Here, we propose and validate algorithms to perform this task, at runtime, from the raw physical channel of an operative mobile network, without having to decode and/or decrypt the transmitted flows. T…
New method for robust PCA with exponential family distributions.
Study uses satellite and lidar data to map forest height and biomass in France.
Post-pandemic, work patterns shifted with fewer days in offices and a new midweek mountain.
Traffic congestion in metropolitan areas is a world-wide problem that can be ameliorated by traffic lights that respond dynamically to real-time conditions. Recent studies applying deep reinforcement learning (RL) to optimize single traffic lights have shown significant improvement over conventional control. However, o…
Urban2Vec combines street view imagery and POIs for better urban neighborhood embeddings.
A large GPS dataset reveals that a single route often covers 60% of travel observations.
This paper investigates the risk-return relationship in determination of housing asset pricing. In so doing, the paper evaluates behavioral hypotheses advanced by Case and Shiller (1988, 2002, 2009) in studies of boom and post-boom housing markets. The paper specifies and tests a multi-factor housing asset pricing mode…
The dynamic nature of air quality chemistry and transport makes it difficult to identify the mixture of air pollutants for a region. In this study of air quality in the Houston metropolitan area we apply dynamic principal component analysis (DPCA) to a normalized multivariate time series of daily concentration measurem…
Archaeologists are in dire need of automated object reconstruction methods. Fragments reassembly is close to puzzle problems, which may be solved by computer vision algorithms. As they are often beaten on most image related tasks by deep learning algorithms, we study a classification method that can solve jigsaw puzzle…
Study improves dynamic PT fleet optimization under noisy demand predictions.
The increasing penetration of distributed energy resources poses numerous reliability issues to the urban distribution grid. The topology estimation is a critical step to ensure the robustness of distribution grid operation. However, the bus connectivity and grid topology estimation are usually hard in distribution gri…
GraphSVR forecasts urban air pollution robustly across stations and seasons.
IGANI uses iterative GANs to improve traffic data imputation.
NeuroPaint infers missing brain area dynamics from multi-animal datasets.
In this paper, we introduce the geominimal surface area for all , which extends the classical geominimal surface area () by Petty and the geominimal surface area by Lutwak (). Our extension of the geominimal surface area is motivated by recent work on the extension of the a…
Overview of affine surface area and its history.
Hasse principle applied to area-minimizing submanifolds across different homology types.
Two families of general affine surface areas are introduced. Basic properties and affine isoperimetric inequalities for these new affine surface areas as well as for affine surface areas are established.
The hermitian analog of Aleksandrov's area measures of convex bodies is investigated. A characterization of those area measures which arise as the first variation of unitarily invariant valuations is established. General smooth area measures are shown to form a module over smooth valuations and the module of unitarily …
BiLipschitz mappings can be extended to preserve area.
Formula for Heisenberg group surface areas derived.
Introduces new weighted floating functions and affine surface areas.
Study minimal annuli in a slab, estimating their area.
Study area-minimizing subgraphs in integer lattices.
Existing attention mechanisms are trained to attend to individual items in a collection (the memory) with a predefined, fixed granularity, e.g., a word token or an image grid. We propose area attention: a way to attend to areas in the memory, where each area contains a group of items that are structurally adjacent, e.g…
Minimal surfaces in hyperbolic space have a renormalized area criterion.
Upper bounds on area for surfaces with constant mean curvature in hyperbolic 3-manifolds.
Study shows area-minimizing submanifolds are mostly rough, not smooth.