Picture for James G. Scott

James G. Scott

Conditional diffusions for neural posterior estimation

Add code
Oct 24, 2024
Viaarxiv icon

Interpretable Low-Dimensional Regression via Data-Adaptive Smoothing

Add code
Aug 06, 2017
Figure 1 for Interpretable Low-Dimensional Regression via Data-Adaptive Smoothing
Figure 2 for Interpretable Low-Dimensional Regression via Data-Adaptive Smoothing
Viaarxiv icon

Deep Nonparametric Estimation of Discrete Conditional Distributions via Smoothed Dyadic Partitioning

Add code
Feb 28, 2017
Figure 1 for Deep Nonparametric Estimation of Discrete Conditional Distributions via Smoothed Dyadic Partitioning
Figure 2 for Deep Nonparametric Estimation of Discrete Conditional Distributions via Smoothed Dyadic Partitioning
Figure 3 for Deep Nonparametric Estimation of Discrete Conditional Distributions via Smoothed Dyadic Partitioning
Figure 4 for Deep Nonparametric Estimation of Discrete Conditional Distributions via Smoothed Dyadic Partitioning
Viaarxiv icon

GapTV: Accurate and Interpretable Low-Dimensional Regression and Classification

Add code
Feb 23, 2017
Figure 1 for GapTV: Accurate and Interpretable Low-Dimensional Regression and Classification
Figure 2 for GapTV: Accurate and Interpretable Low-Dimensional Regression and Classification
Figure 3 for GapTV: Accurate and Interpretable Low-Dimensional Regression and Classification
Figure 4 for GapTV: Accurate and Interpretable Low-Dimensional Regression and Classification
Viaarxiv icon

Diet2Vec: Multi-scale analysis of massive dietary data

Add code
Dec 01, 2016
Figure 1 for Diet2Vec: Multi-scale analysis of massive dietary data
Figure 2 for Diet2Vec: Multi-scale analysis of massive dietary data
Figure 3 for Diet2Vec: Multi-scale analysis of massive dietary data
Figure 4 for Diet2Vec: Multi-scale analysis of massive dietary data
Viaarxiv icon

Better Conditional Density Estimation for Neural Networks

Add code
Jun 07, 2016
Figure 1 for Better Conditional Density Estimation for Neural Networks
Figure 2 for Better Conditional Density Estimation for Neural Networks
Figure 3 for Better Conditional Density Estimation for Neural Networks
Figure 4 for Better Conditional Density Estimation for Neural Networks
Viaarxiv icon

Tensor decomposition with generalized lasso penalties

Add code
May 13, 2016
Figure 1 for Tensor decomposition with generalized lasso penalties
Figure 2 for Tensor decomposition with generalized lasso penalties
Figure 3 for Tensor decomposition with generalized lasso penalties
Figure 4 for Tensor decomposition with generalized lasso penalties
Viaarxiv icon

Priors for Random Count Matrices Derived from a Family of Negative Binomial Processes

Add code
Jul 13, 2015
Figure 1 for Priors for Random Count Matrices Derived from a Family of Negative Binomial Processes
Figure 2 for Priors for Random Count Matrices Derived from a Family of Negative Binomial Processes
Figure 3 for Priors for Random Count Matrices Derived from a Family of Negative Binomial Processes
Figure 4 for Priors for Random Count Matrices Derived from a Family of Negative Binomial Processes
Viaarxiv icon

A Fast and Flexible Algorithm for the Graph-Fused Lasso

Add code
Jun 01, 2015
Figure 1 for A Fast and Flexible Algorithm for the Graph-Fused Lasso
Figure 2 for A Fast and Flexible Algorithm for the Graph-Fused Lasso
Figure 3 for A Fast and Flexible Algorithm for the Graph-Fused Lasso
Figure 4 for A Fast and Flexible Algorithm for the Graph-Fused Lasso
Viaarxiv icon

Proximal Algorithms in Statistics and Machine Learning

Add code
May 30, 2015
Figure 1 for Proximal Algorithms in Statistics and Machine Learning
Figure 2 for Proximal Algorithms in Statistics and Machine Learning
Figure 3 for Proximal Algorithms in Statistics and Machine Learning
Figure 4 for Proximal Algorithms in Statistics and Machine Learning
Viaarxiv icon