Sander van Cranenburgh

22 papers Journal 16Unranked 6
YearRankTypeTitle / Venue / Authors
2025 — conf
An image embedding-based approach for classifying street networks.
SIGSPATIAL/GIS
Francisco Garrido-Valenzuela, Max Lange, Juan Carlos Herrera, Sander van Cranenburgh, Oded Cats
2025 J jnl
Can large language models assist choice modelling? Insights into prompting strategies and current models capabilities.
CoRR
Georges Sfeir, Gabriel Nova, Stephane Hess, Sander van Cranenburgh
2025 J jnl
Improving choice model specification using reinforcement learning.
CoRR
Gabriel Nova, Sander van Cranenburgh, Stephane Hess
2025 J jnl
Learning Collision Risk from Naturalistic Driving with Generalised Surrogate Safety Measures.
CoRR
Yiru Jiao, Simeon C. Calvert, Sander van Cranenburgh, Hans van Lint
2025 J jnl
Structure-preserving contrastive learning for spatial time series.
CoRR
Yiru Jiao, Sander van Cranenburgh, Simeon C. Calvert, Hans van Lint
2025 J jnl
Studying riots through the lens of social media.
J. Big Data
Lucas Spierenburg, Sander van Cranenburgh, Oded Cats
2024 J jnl
A unified theory and statistical learning approach for traffic conflict detection.
CoRR
Yiru Jiao, Simeon C. Calvert, Sander van Cranenburgh, Hans van Lint
2024 J jnl
A utility-based spatial analysis of residential street-level conditions; A case study of Rotterdam.
CoRR
Sander van Cranenburgh, Francisco Garrido-Valenzuela
2024 J jnl
An economically-consistent discrete choice model with flexible utility specification based on artificial neural networks.
CoRR
Jose Ignacio Hernandez, Niek Mouter, Sander van Cranenburgh
2024 J jnl
Integral system safety for machine learning in the public sector: An empirical account.
Gov. Inf. Q.
Jeroen Delfos, Anneke Zuiderwijk-van Eijk, Sander van Cranenburgh, Caspar G. Chorus, Roel I. J. Dobbe
2024 J jnl
Understanding the decision-making process of choice modellers.
CoRR
Gabriel Nova, Sander van Cranenburgh, Stephane Hess
2023 J jnl
Characterizing residential segregation in cities using intensity, separation, and scale indicators.
Comput. Environ. Urban Syst.
Lucas Spierenburg, Sander van Cranenburgh, Oded Cats
2023 J jnl
Computer vision-enriched discrete choice models, with an application to residential location choice.
CoRR
Sander van Cranenburgh, Francisco Garrido-Valenzuela
2023 — conf
Identifying Vehicle Interaction at Urban Intersections: A Comparison of Proximity Resistance, Time-to-Collision, and Post-Encroachment-Time.
ITSC
Yiru Jiao, Simeon C. Calvert, Hans van Lint, Sander van Cranenburgh
2023 J jnl
Where are the people? Counting people in millions of street-level images to explore associations between people's urban density and urban characteristics.
Comput. Environ. Urban Syst.
Francisco Garrido-Valenzuela, Oded Cats, Sander van Cranenburgh
2022 — conf
A regionalization method filtering out small-scale spatial fluctuations.
AGILE Conf.
Lucas Spierenburg, Sander van Cranenburgh, Oded Cats
2022 — conf
Enriching geospatial data with computer vision to identify urban environment determinants of social interactions.
AGILE Conf.
Francisco Garrido-Valenzuela, Sander van Cranenburgh, Oded Cats
2022 J jnl
Explainability of Deep Learning models for Urban Space perception.
CoRR
Ruben Sangers, Jan van Gemert, Sander van Cranenburgh
2022 — conf
Perceived challenges and opportunities of machine learning applications in governmental organisations: an interview-based exploration in the Netherlands.
ICEGOV
Jeroen Delfos, Anneke Zuiderwijk, Sander van Cranenburgh, Caspar G. Chorus
2021 J jnl
Choice modelling in the age of machine learning.
CoRR
Sander van Cranenburgh, Shenhao Wang, Akshay Vij, Francisco Pereira, Joan Walker
2021 J jnl
Obfuscation maximization-based decision-making: Theory, methodology and first empirical evidence.
Math. Soc. Sci.
Caspar G. Chorus, Sander van Cranenburgh, Aemiro Melkamu Daniel, Erlend Dancke Sandorf, Anae Sobhani, Teodóra Szép
2019 — conf
Using Artificial Neural Networks for Recovering the Value-of-Travel-Time Distribution.
IWANN (1)
Sander van Cranenburgh, Marco Kouwenhoven