A Data-Driven Method for OD Matrix Estimation
A clear walkthrough of a data-driven origin-destination matrix estimation method that uses traffic speeds, flows, production-attraction patterns, shortest paths, and PCA.
Blog Topic
Technical Articles
Technical articles, paper summaries, and research notes spanning AI, transportation, demand forecasting, and planning.
Data-Driven Structural Fire Risk Prediction for City Properties
A practical look at how machine learning can help fire departments prioritize property inspections using historical fire incidents, violations, inspections, and property data.
Guidance on Value of Statistical Life (VSL) in Economic Analysis
A clear explanation of how the U.S. Department of Transportation uses the Value of a Statistical Life to measure safety benefits in economic analysis.
Giving AI Some Common Sense
A readable reflection on Ron Brachman's Northeastern lecture about why AI systems need common sense before they can be trusted to act autonomously.
Predictions for abundant, awesome, technology-based, Possible Tomorrows (2035-2049)
A more grounded look at Vinod Khosla's TED 2024 vision for technology-driven possible tomorrows between 2035 and 2049.
Interval Temporal Logic Decision Tree Learning
A readable explanation of Temporal ID3, a decision-tree learning method that uses interval temporal logic to classify timelines instead of static records.
Towards a General Method for Logical Rule Extraction from Time Series
A readable explanation of a general pipeline for turning multivariate time series into timelines and extracting temporal logical rules from them.
A Brief Overview of Rule Learning
A readable overview of rule learning, including descriptive rule discovery, predictive rule learning, association rules, decision lists, and covering algorithms.
Distilling Free-Form Natural Laws from Experimental Data
A readable look at how symbolic regression can rediscover physical laws directly from experimental data, from simple oscillators to chaotic double pendulums.