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.
Study proposes CNN for reconstructing high-res urban DEMs.
Mathematical problems of digital terrain analysis include interpolation of digital elevation models (DEMs), DEM generalization and denoising, and computation of morphometric variables by calculation of partial derivatives of elevation. Traditionally, these procedures are based on numerical treatments of two-variable di…
The family of Expectation-Maximization (EM) algorithms provides a general approach to fitting flexible models for large and complex data. The expectation (E) step of EM-type algorithms is time-consuming in massive data applications because it requires multiple passes through the full data. We address this problem by pr…
Paper proposes a new AI design philosophy for distributed learning.
Online DEM improves tracking of latent states in dynamic systems.
A long-standing question for urban and regional planners pertains to the ability to describe urban patterns quantitatively. Cities' transport infrastructure, particularly street networks, provides an invaluable source of information about the urban patterns generated by peoples' movements and their interactions. With t…
UrbanRhythm reveals urban dynamics from mobility data.
Survey of urban flows prediction methods using various datasets.
Graph embeddings from commute networks identify socioeconomic disparities in urban areas.
CityTFT models urban building energy using a data-driven approach.
Paper uses DeePC to improve urban traffic lights, reducing congestion and emissions.
New approach for large-scale distributed learning systems that improve generalization performance.
Understanding the causes of crime is a longstanding issue in researcher's agenda. While it is a hard task to extract causality from data, several linear models have been proposed to predict crime through the existing correlations between crime and urban metrics. However, because of non-Gaussian distributions and multic…
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…
The evolution of the probability distributions of Japan and US major market indices, NIKKEI 225 and NASDAQ composite index, and and currency exchange rates is described by means of the Fokker-Planck equation (FPE). In order to distinguish and quantify the deterministic and random influences on these…
Model predicts traffic speed using urban incidents.
Novel graph model forecasts urban traffic with reduced spatial complexity.
Recent years have witnessed the world-wide emergence of mega-metropolises with incredibly huge populations. Understanding residents mobility patterns, or urban dynamics, thus becomes crucial for building modern smart cities. In this paper, we propose a Neighbor-Regularized and context-aware Non-negative Tensor Factoriz…
hood2vec identifies urban area similarity via mobility networks.
The paper uses GIS data to predict urban sprawl.
Paper optimizes urban navigation with deep learning models.
Deep learning agent improves pedestrian navigation in urban environments.
Novel RL method handles urban driving tasks including traffic lights.
Machine learning uncovers hidden correlations in granular material behavior.
Bayesian network framework assesses urban risks across multiple domains.
AirRL uses RL to infer urban air quality from selected stations.
Quantile regression improves urban water demand forecasting.
Deep generative models are commonly used for generating images and text. Interpretability of these models is one important pursuit, other than the generation quality. Variational auto-encoder (VAE) with Gaussian distribution as prior has been successfully applied in text generation, but it is hard to interpret the mean…
Cultural activity is an inherent aspect of urban life and the success of a modern city is largely determined by its capacity to offer generous cultural entertainment to its citizens. To this end, the optimal allocation of cultural establishments and related resources across urban regions becomes of vital importance, as…
New model predicts urban sprawl sensitivity from remote sensing data.
Deep Recurrent Q-Network improves autonomous driving in urban areas with pedestrians.
This paper examines the intra-day seasonality of transacted limit and market orders in the DEM/USD foreign exchange market. Empirical analysis of completed transactions data based on the Dealing 2000-2 electronic inter-dealer broking system indicates significant evidence of intraday seasonality in returns and return vo…
While it is believed that denoising is not always necessary in many big data applications, we show in this paper that denoising is helpful in urban traffic analysis by applying the method of bounded total variation denoising to the urban road traffic prediction and clustering problem. We propose two easy-to-implement m…
Intensive development of urban systems creates a number of challenges for urban planners and policy makers in order to maintain sustainable growth. Running efficient urban policies requires meaningful urban metrics, which could quantify important urban characteristics including various aspects of an actual human behavi…
In this paper we seek methods to effectively detect urban micro-events. Urban micro-events are events which occur in cities, have limited geographical coverage and typically affect only a small group of citizens. Because of their scale these are difficult to identify in most data sources. However, by using citizen sens…
Study shows income inequality increases with city size, affecting only the wealthiest deciles.
Paper presents a simple method for accurate user localization in urban areas.
MIP framework improves urban flow prediction by adapting to distribution shifts.
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…
Generative model learns vehicle trajectory distributions for better data generalization.
Paper presents UrbanFM and UrbanPy models for inferring fine-grained urban flows.
Study of urban lifestyles from mobility data of 1.2M people in 11 U.S. cities.
I propose and briefly define the concept of Urban Isobenefit Lines by using functions as easy as efficient, whose results can offer a rich tool to use into spatial equilibrium analysis involving cities. They are line joining urban points with equal level of positional advantage from city amenities. The results which on…
Bike usage in Smart Cities becomes paramount for sustainable urban development. Cycling provides tremendous opportunities for a more healthy lifestyle, lower energy consumption and carbon emissions as well as reduction of traffic jams. While the number of cyclists increase along with the expansion of bike sharing initi…
Study identifies spatial inequalities in urban services access based on income.
Because of the prominent position of urban rail in reducing urban transport-related problems, such as congestion and air pollution, insights into the costs of possible new urban rail projects is very relevant for those involved with cost estimations, policy makers, cost-benefit analysts, and other target groups. Knowle…
Model predicts urban population using mobile data traffic.
Paper proposes a method for predicting future passenger flow in urban transportation.