Copertina

Geospatial Road Cycling Race Results Data Set

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Janssens, Bram, Pappalardo, Luca, De Bock, Jelle, Bogaert, Matthias, Verstockt, Steven
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computers and Society Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Bike2Vec: Vector Embedding Representations of Road Cycling Riders and Races
di: Baron, Ethan, et al.
Pubblicazione: (2023)

LLM-Assisted Topic Reduction for BERTopic on Social Media Data
di: Janssens, Wannes, et al.
Pubblicazione: (2025)

An Ensemble Framework for Explainable Geospatial Machine Learning Models
di: Liu, Lingbo
Pubblicazione: (2024)

General Geospatial Inference with a Population Dynamics Foundation Model
di: Agarwal, Mohit, et al.
Pubblicazione: (2024)

Geospatial Disparities: A Case Study on Real Estate Prices in Paris
di: Machado, Agathe Fernandes, et al.
Pubblicazione: (2024)

InstaGeo: Compute-Efficient Geospatial Machine Learning from Data to Deployment
di: Yusuf, Ibrahim Salihu, et al.
Pubblicazione: (2025)

Active Geospatial Search for Efficient Tenant Eviction Outreach
di: Sarkar, Anindya, et al.
Pubblicazione: (2024)

SX-GeoTree: Self-eXplaining Geospatial Regression Tree Incorporating the Spatial Similarity of Feature Attributions
di: Kang, Chaogui, et al.
Pubblicazione: (2025)

Applications of Trajectory Data from the Perspective of a Road Transportation Agency: Literature Review and Maryland Case Study
di: Marković, Nikola, et al.
Pubblicazione: (2017)

A Recurrent Neural Network based Clustering Method for Binary Data Sets in Education
di: Ohira, Mizuki, et al.
Pubblicazione: (2025)

Cycling into the workshop: predictive maintenance for Barcelona's bike-sharing system
di: Grau-Escolano, Jordi, et al.
Pubblicazione: (2024)

LSTM+Geo with xgBoost Filtering: A Novel Approach for Race and Ethnicity Imputation with Reduced Bias
di: Chalavadi, S., et al.
Pubblicazione: (2025)

Role and Use of Race in AI/ML Models Related to Health
di: Were, Martin C., et al.
Pubblicazione: (2025)

Towards Human-AI Complementarity with Prediction Sets
di: De Toni, Giovanni, et al.
Pubblicazione: (2024)

Optimal Transport for Fairness: Archival Data Repair using Small Research Data Sets
di: Langbridge, Abigail, et al.
Pubblicazione: (2024)

Beyond AlphaEarth: Toward Human-Centered Geospatial Foundation Models via POI-Guided Contrastive Learning
di: Liu, Junyuan, et al.
Pubblicazione: (2025)

OGD4All: A Framework for Accessible Interaction with Geospatial Open Government Data Based on Large Language Models
di: Siebenmann, Michael, et al.
Pubblicazione: (2025)

From Street Views to Urban Science: Discovering Road Safety Factors with Multimodal Large Language Models
di: Tang, Yihong, et al.
Pubblicazione: (2025)

Prediction without Preclusion: Recourse Verification with Reachable Sets
di: Kothari, Avni, et al.
Pubblicazione: (2023)

On the Effectiveness and Generalization of Race Representations for Debiasing High-Stakes Decisions
di: Nguyen, Dang, et al.
Pubblicazione: (2025)

Mining patterns in syntax trees to automate code reviews of student solutions for programming exercises
di: Van Petegem, Charlotte, et al.
Pubblicazione: (2024)

Be Intentional About Fairness!: Fairness, Size, and Multiplicity in the Rashomon Set
di: Dai, Gordon, et al.
Pubblicazione: (2025)

Breaking the Cycle of Incarceration With Targeted Mental Health Outreach: A Case Study in Machine Learning for Public Policy
di: Rodolfa, Kit T., et al.
Pubblicazione: (2025)

A Clinical Trial Design Approach to Auditing Language Models in Healthcare Setting
di: Gondara, Lovedeep, et al.
Pubblicazione: (2024)

Geometry of Relaxed Fair Regression: A Unified Framework for Aware and Unaware Settings
di: Lince, M. Generali, et al.
Pubblicazione: (2026)

What's in a Name? Auditing Large Language Models for Race and Gender Bias
di: Salinas, Alejandro, et al.
Pubblicazione: (2024)

Comparing Data Assimilation and Likelihood-Based Inference on Latent State Estimation in Agent-Based Models
di: Kolic, Blas, et al.
Pubblicazione: (2025)

Time Series Foundation Models are Flow Predictors
di: Luca, Massimiliano, et al.
Pubblicazione: (2025)

EduGym: An Environment and Notebook Suite for Reinforcement Learning Education
di: Moerland, Thomas M., et al.
Pubblicazione: (2023)

Hypothesis Testing for Quantifying LLM-Human Misalignment in Multiple Choice Settings
di: Hong, Harbin, et al.
Pubblicazione: (2025)

Should I use Synthetic Data for That? An Analysis of the Suitability of Synthetic Data for Data Sharing and Augmentation
di: Kulynych, Bogdan, et al.
Pubblicazione: (2026)

Uncertainty-Aware Probabilistic Graph Neural Networks for Road-Level Traffic Accident Prediction
di: Gao, Xiaowei, et al.
Pubblicazione: (2023)

Measurement as Bricolage: Examining How Data Scientists Construct Target Variables for Predictive Modeling Tasks
di: Guerdan, Luke, et al.
Pubblicazione: (2025)

Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection
di: Jain, Saachi, et al.
Pubblicazione: (2024)

Rethinking Anonymity Claims in Synthetic Data Generation: A Model-Centric Privacy Attack Perspective
di: Ganev, Georgi, et al.
Pubblicazione: (2026)

CycleResearcher: Improving Automated Research via Automated Review
di: Weng, Yixuan, et al.
Pubblicazione: (2024)

Evaluating Large Language Model Capabilities in Assessing Spatial Econometrics Research
di: Arbia, Giuseppe, et al.
Pubblicazione: (2025)

Navigating Towards Fairness with Data Selection
di: Zhang, Yixuan, et al.
Pubblicazione: (2024)

A Principled Approach for Data Bias Mitigation
di: Scarone, Bruno, et al.
Pubblicazione: (2024)

Achievable Fairness on Your Data With Utility Guarantees
di: Taufiq, Muhammad Faaiz, et al.
Pubblicazione: (2024)