68 citations · 77 across the 10 of their papers we have counts for
10 papers
Spatiotemporal Modeling and Forecasting at Scale with Dynamic Generalized Linear Models
Pranay Pherwani, Nicholas Hass, Anna K. Yanchenko
Spatiotemporal data consisting of timestamps, GPS coordinates, and IDs occurs in many settings. Modeling approaches for this type of data must address challenges in terms of sensor…
Reply to Discussions of "Multivariate Dynamic Modeling for Bayesian Forecasting of Business Revenue"
Anna K. Yanchenko, Graham Tierney, Joseph Lawson +3
We are most grateful to all discussants for their positive comments and many thought-provoking questions. In addition, the discussants provide a number of useful leads into various…
Multivariate Dynamic Modeling for Bayesian Forecasting of Business Revenue
Anna K. Yanchenko, Graham Tierney, Joseph Lawson +3
Forecasting enterprise-wide revenue is critical to many companies and presents several challenges and opportunities for significant business impact. This case study is based on mod…
A Methodology for Exploring Deep Convolutional Features in Relation to Hand-Crafted Features with an Application to Music Audio Modeling
Anna K. Yanchenko, Mohammadreza Soltani, Robert J. Ravier +2
Understanding the features learned by deep models is important from a model trust perspective, especially as deep systems are deployed in the real world. Most recent approaches for…
Hierarchical Dynamic Modeling for Individualized Bayesian Forecasting
Anna K. Yanchenko, Di Daniel Deng, Jinglan Li +2
We present a case study and methodological developments in large-scale hierarchical dynamic modeling for personalized prediction in commerce. The context is supermarket sales, wher…
Network Analysis of Orchestral Concert Programming
Anna K. Yanchenko
Orchestral concert programming is a challenging, yet critical task for expanding audience engagement and is usually driven by qualitative heuristics and common musical practices. Q…
Stanza: A Nonlinear State Space Model for Probabilistic Inference in Non-Stationary Time Series
Anna K. Yanchenko, Sayan Mukherjee
Time series with long-term structure arise in a variety of contexts and capturing this temporal structure is a critical challenge in time series analysis for both inference and for…
Hierarchical Multidimensional Scaling for the Comparison of Musical Performance Styles
Anna K. Yanchenko, Peter D. Hoff
Quantification of stylistic differences between musical artists is of academic interest to the music community, and is also useful for other applications such as music information…
Classical Music Composition Using State Space Models
Anna K. Yanchenko, Sayan Mukherjee
Algorithmic composition of music has a long history and with the development of powerful deep learning methods, there has recently been increased interest in exploring algorithms a…
Predicting Exploitation of Disclosed Software Vulnerabilities Using Open-source Data
Benjamin L. Bullough, Anna K. Yanchenko, Christopher L. Smith +1
Each year, thousands of software vulnerabilities are discovered and reported to the public. Unpatched known vulnerabilities are a significant security risk. It is imperative that s…