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arXiv research

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.

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7 results for Melbourne

Predicting ambulance demand accurately at a fine resolution in time and space (e.g., every hour and 1 km2^2) is critical for staff / fleet management and dynamic deployment. There are several challenges: though the dataset is typically large-scale, demand per time period and locality is almost always zero. The demand …

2016-06-16abs ↗pdf ↗

A new house price prediction model using location data and multi-task learning.

problem Accurate house price prediction for various stakeholders.
method Location-centered data profiling and Multi-Task Learning (MTL) approach.
result MTL-based methods significantly outperform state-of-the-art approaches in house price prediction.

Generative adversarial networks transform streetscape images to improve health and wellbeing.

problem Improving health and wellbeing outcomes through better streetscape design.
method Generative adversarial networks were used to translate Google Street View images, preserving structure while changing the style from bad health to good health areas.
result Translated images show that good health areas have more green space and compact urban design, while good social capital areas have more footpaths and less fencing.