Additive Nonparametric Regression with Spatial and Network Objects

arXiv:2609.26867 · stat.ME, stat.AP, stat.ML · Submitted 2026-09-22 · Read on arXiv

stat.ME, stat.AP, stat.ML

Submitted: 2026-09-22

Updated: 2026-09-22

Code: https://github.com/pritamdey/AMOGP

Terminology

• Accuracy — 10× in this paper · explained in 1 episode
• Consistency — 10× in this paper · explained in 3 episodes
• Adolescent Brain Cognitive Development — 4× in this paper
• Alignment — 4× in this paper · explained in 1 episode
• Neural Network — 4× in this paper
• Bayesian Framework — 2× in this paper · explained in 3 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Hilbert Space — 2× in this paper · explained in 2 episodes
• Markov Chain Monte Carlo — 2× in this paper
• Mean Squared Prediction Error — 2× in this paper
• Robustness — 2× in this paper · explained in 5 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Uncertainty Quantification — 2× in this paper · explained in 8 episodes
• Adjacency Matrix — 1× in this paper · explained in 1 episode
• Aphasia — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reproducing Kernel Hilbert Space (RKHS) — 1× in this paper · explained in 3 episodes
• Two-Stage Framework — 1× in this paper · explained in 2 episodes

Sources

• A tensor based varying-coefficient model for multi-modal neuroimaging data analysis

Related papers

• Doubly robust inference via calibration
• Bayesian Empirical Bayes: Simultaneous Inference from Probabilistic Symmetries
• Flexible Nonparametric Inference for Causal Effects under the Front-Door Model
• Deployment of AI-Assisted Interventions: Capacity Constraints and Noisy Compliance
• A Survey on Archetypal Analysis
• Dynamic Spatial Bayesian Machine Learning Model: Applications to Intergenerational Economic Mobility and Geographic Income Inequality in the United States