James G. Scott

According to our database, James G. Scott authored at least 13 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Conditional diffusions for neural posterior estimation.

Tianyu Chen, Vansh Bansal, James G. Scott

CoRR, 2024

2023

Weather2vec: Representation Learning for Causal Inference with Non-local Confounding in Air Pollution and Climate Studies.

Mauricio Tec, James G. Scott, Corwin M. Zigler

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2021

Combining spatial and sociodemographic regression techniques to predict residential fire counts at the census tract level.

Tyler Buffington, James G. Scott, Ofodike A. Ezekoye

Comput. Environ. Urban Syst., 2021

2020

Socioeconomic bias in influenza surveillance.

Samuel V. Scarpino, James G. Scott, Rosalind M. Eggo, Bruce Clements, Nedialko B. Dimitrov, Lauren Ancel Meyers

PLoS Comput. Biol., 2020

2018

TDAstats: R pipeline for computing persistent homology in topological data analysis.

Raoul R. Wadhwa, Drew F. K. Williamson, Andrew Dhawan, James G. Scott

J. Open Source Softw., 2018

Maximum-Variance Total Variation Denoising for Interpretable Spatial Smoothing.

Wesley Tansey, Jesse Thomason, James G. Scott

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Leaf-Smoothed Hierarchical Softmax for Ordinal Prediction.

Wesley Tansey, Karl Pichotta, James G. Scott

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

The DFS Fused Lasso: Linear-Time Denoising over General Graphs.

Oscar Hernan Madrid Padilla, James Sharpnack, James G. Scott, Ryan J. Tibshirani

J. Mach. Learn. Res., 2017

2016

Diet2Vec: Multi-scale analysis of massive dietary data.

Wesley Tansey, Edward W. Lowe Jr., James G. Scott

CoRR, 2016

2015

Proximal Algorithms in Statistics and Machine Learning.

Nicholas G. Polson, James G. Scott, Brandon T. Willard

CoRR, 2015

2012

Benchmarking historical corporate performance.

James G. Scott

Comput. Stat. Data Anal., 2012

Fully Bayesian inference for neural models with negative-binomial spiking.

Jonathan W. Pillow, James G. Scott

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2009

Handling Sparsity via the Horseshoe.

Carlos M. Carvalho, Nicholas G. Polson, James G. Scott

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009