Cover Image

Data-Driven Framework Development for Public Space Quality Assessment

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Turaev, Sherzod, John, Mary
Format:	Preprint
Published:	2025
Subjects:	Computers and Society Digital Libraries Information Retrieval 68W05, 62P12, G.3; I.5.3
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TimeGraph: Synthetic Benchmark Datasets for Robust Time-Series Causal Discovery
by: Ferdous, Muhammad Hasan, et al.
Published: (2025)

Scalable Bayesian Clustering for Integrative Analysis of Multi-View Data
by: Cabral, Rafael, et al.
Published: (2024)

Perception-Aware Bias Detection for Query Suggestions
by: Haak, Fabian, et al.
Published: (2026)

Data-Driven Discovery of Feature Groups in Clinical Time Series
by: Sergeev, Fedor, et al.
Published: (2025)

Can We Trust AI-Inferred User States. A Psychometric Framework for Validating the Reliability of Users States Classification by LLMs in Operational Environments
by: Krzeminska, Izabella, et al.
Published: (2026)

Boxplots and quartile plots for grouped and periodic angular data
by: Berlinski, Joshua D., et al.
Published: (2026)

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization
by: Raichur, Nisha Lakshmana, et al.
Published: (2025)

Enhanced Single-Cell RNA-seq Embedding through Gene Expression and Data-Driven Gene-Gene Interaction Integration
by: Goudarzi, Hojjat Torabi, et al.
Published: (2025)

Evaluating the Quality of the Quantified Uncertainty for (Re)Calibration of Data-Driven Regression Models
by: Wibbeke, Jelke, et al.
Published: (2025)

Proximity Measure of Information Object Features for Solving the Problem of Their Identification in Information Systems
by: Yuzefovych, Volodymyr
Published: (2026)

Iterative Exploration-Driven Sparse SDP Clustering via Thompson Sampling
by: Mun, Jongmin, et al.
Published: (2025)

Signature-Kernel Based Evaluation Metrics for Robust Probabilistic and Tail-Event Forecasting
by: Redhead, Benjamin R., et al.
Published: (2026)

Bridging Human Cognition and AI: A Framework for Explainable Decision-Making Systems
by: Jean, N., et al.
Published: (2025)

Careful Seeding for k-Medois Clustering with Incremental k-Means++ Initialization
by: Cheng, Difei, et al.
Published: (2022)

From Point to probabilistic gradient boosting for claim frequency and severity prediction
by: Chevalier, Dominik, et al.
Published: (2024)

DeepCausalMMM: A Deep Learning Framework for Marketing Mix Modeling with Causal Structure Learning
by: Tirumala, Aditya Puttaparthi
Published: (2025)

Data-Adaptive Low-Rank Sparse Subspace Clustering
by: Kopriva, Ivica
Published: (2025)

Multiple data-driven missing imputation
by: Kavun, Sergii
Published: (2025)

Ranking of Multi-Response Experiment Treatments
by: Pebes-Trujillo, Miguel R., et al.
Published: (2024)

Machine Collaboration
by: Liu, Qingfeng, et al.
Published: (2021)

Measures of Overlapping Multivariate Gaussian Clusters in Unsupervised Online Learning
by: Ožbot, Miha, et al.
Published: (2025)

An arithmetic method algorithm optimizing k-nearest neighbors compared to regression algorithms and evaluated on real world data sources
by: Anagnostopoulos, Theodoros, et al.
Published: (2026)

Differentially Private Truncation of Unbounded Data via Public Second Moments
by: Cao, Zilong, et al.
Published: (2026)

An AutoML Framework using AutoGluonTS for Forecasting Seasonal Extreme Temperatures
by: Rodríguez-Bocca, Pablo, et al.
Published: (2025)

Data-driven quasi-interpolant spline surfaces for point cloud approximation
by: Raffo, Andrea, et al.
Published: (2019)

Spatiotemporal k-means
by: Dorabiala, Olga, et al.
Published: (2022)

TNStream: Applying Tightest Neighbors to Micro-Clusters to Define Multi-Density Clusters in Streaming Data
by: Zeng, Qifen, et al.
Published: (2025)

Advancing Annotat3D with Harpia: A CUDA-Accelerated Library For Large-Scale Volumetric Data Segmentation
by: de Araujo, Camila Machado, et al.
Published: (2025)

Physics-informed machine learning: A mathematical framework with applications to time series forecasting
by: Doumèche, Nathan
Published: (2025)

A Reproducible, Scalable Pipeline for Synthesizing Autoregressive Model Literature
by: Alpay, Faruk, et al.
Published: (2025)

Dynamic Regularized CBDT: Variance-Calibrated Causal Boosting for Interpretable Heterogeneous Treatment Effects
by: Liu, Yichen
Published: (2025)

On the Accuracy of Newton Step and Influence Function Data Attributions
by: Rubinstein, Ittai, et al.
Published: (2025)

Augmented Functional Random Forests: Classifier Construction and Unbiased Functional Principal Components Importance through Ad-Hoc Conditional Permutations
by: Maturo, Fabrizio, et al.
Published: (2024)

Extensions of the regret-minimization algorithm for optimal design
by: Chen, Youguang, et al.
Published: (2025)

ACTGNN: Assessment of Clustering Tendency with Synthetically-Trained Graph Neural Networks
by: Luo, Yiran, et al.
Published: (2025)

Evaluation of the number of clusters in a data set using $p$-values from Multiple Tests of Hypotheses
by: Modak, Soumita
Published: (2026)

A Bayesian Updating Framework for Long-term Multi-Environment Trial Data in Plant Breeding
by: Bark, Stephan, et al.
Published: (2026)

LLM-based IR-system for Bank Supervisors
by: Aarab, Ilias
Published: (2025)

A Hybrid Mixture Approach for Clustering and Characterizing Cancer Data
by: Kareem, Kazeem, et al.
Published: (2025)

Pair Correlation Factor and the Sample Complexity of Gaussian Mixtures
by: Aryan, Farzad
Published: (2025)