Cover Image

Scalable Spatiotemporal Prediction with Bayesian Neural Fields

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Saad, Feras, Burnim, Jacob, Carroll, Colin, Patton, Brian, Köster, Urs, Saurous, Rif A., Hoffman, Matthew
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Applications Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Bridging the Unavoidable A Priori: A Framework for Comparative Causal Modeling
by: Hovmand, Peter S., et al.
Published: (2025)

ConfHit: Conformal Generative Design with Oracle Free Guarantees
by: Laghuvarapu, Siddhartha, et al.
Published: (2026)

Estimating Item Difficulty with Large Language Models as Experts
by: Kolesnikova, Diana, et al.
Published: (2026)

Cross-Domain Offshore Wind Power Forecasting: Transfer Learning Through Meteorological Clusters
by: Weisser, Dominic, et al.
Published: (2026)

An Algorithmic Approach for Causal Health Equity: A Look at Race Differentials in Intensive Care Unit (ICU) Outcomes
by: Plecko, Drago, et al.
Published: (2025)

Diffusion Boosted Trees
by: Han, Xizewen, et al.
Published: (2024)

Latency-Response Theory Model: Evaluating Large Language Models via Response Accuracy and Chain-of-Thought Length
by: Xu, Zhiyu, et al.
Published: (2025)

Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer
by: Shirakawa, Toru, et al.
Published: (2024)

Causal Machine Learning for Surgical Interventions
by: Tamo, J. Ben, et al.
Published: (2025)

iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models
by: Chen, Tianyu, et al.
Published: (2023)

Causal Graph Recovery in Neuroimaging through Answer Set Programming
by: Abavisani, Mohammadsajad, et al.
Published: (2025)

Tackling Copyright Issues in AI Image Generation Through Originality Estimation and Genericization
by: Chiba-Okabe, Hiroaki, et al.
Published: (2024)

Fairboard: a quantitative framework for equity assessment of healthcare models
by: Ruffle, James K., et al.
Published: (2026)

Super-Level-Set Regression: Conditional Quantiles via Volume Minimization
by: Braun, Sacha, et al.
Published: (2026)

Detecting Structural Heart Disease from Electrocardiograms via a Generalized Additive Model of Interpretable Foundation-Model Predictors
by: Zhou, Ya, et al.
Published: (2026)

Removing Spurious Correlation from Neural Network Interpretations
by: Fotouhi, Milad, et al.
Published: (2024)

An Optimal House Price Prediction Algorithm: XGBoost
by: Sharma, Hemlata, et al.
Published: (2024)

Scalable Inference for Bayesian Multinomial Logistic-Normal Dynamic Linear Models
by: Saxena, Manan, et al.
Published: (2024)

All Random Features Representations are Equivalent
by: Sernau, Luke, et al.
Published: (2024)

Scalable Spatiotemporal Modeling for Bicycle Count Prediction
by: Yadav, Rishikesh, et al.
Published: (2025)

Image Processing Techniques to Identify and Quantify Spatiotemporal Carbon Cycle Extremes
by: Sharma, Bharat, et al.
Published: (2025)

When prompt perturbations break your A/B test: A valid statistical test for generative surveying
by: Helm, Hayden, et al.
Published: (2026)

A Distribution-Free Framework for Rewrite-Based Human-text Detection via Knockoff Filtering
by: Liu, Yi
Published: (2026)

Robustifying and Selecting Cohort-Appropriate Prognostic Models under Distributional Shifts
by: Bertsimas, Dimitris, et al.
Published: (2026)

Observing the unobserved confounding through its effects: toward randomized trial-like estimates from real-world survival data
by: Stoumpou, Vasiliki, et al.
Published: (2026)

Eligibility-Aware Evidence Synthesis: An Agentic Framework for Clinical Trial Meta-Analysis
by: Zhao, Yao, et al.
Published: (2026)

Auditing Fairness by Betting
by: Chugg, Ben, et al.
Published: (2023)

Forecasting time series with constraints
by: Doumèche, Nathan, et al.
Published: (2025)

LLM-based Agents for Automated Confounder Discovery and Subgroup Analysis in Causal Inference
by: Lee, Po-Han, et al.
Published: (2025)

Language Models as Causal Effect Generators
by: Bynum, Lucius E. J., et al.
Published: (2024)

Generative Bayesian Computation as a Scalable Alternative to Gaussian Process Surrogates
by: Polson, Nick, et al.
Published: (2026)

Is Machine Learning Unsafe and Irresponsible in Social Sciences? Paradoxes and Reconsidering from Recidivism Prediction Tasks
by: Liu, Jianhong, et al.
Published: (2023)

A Bayesian Framework for Post-disruption Travel Time Prediction in Metro Networks
by: Nazemi, Shayan, et al.
Published: (2026)

Hierarchical Sparse Bayesian Multitask Model with Scalable Inference for Microbiome Analysis
by: Zhu, Haonan, et al.
Published: (2025)

Likelihood-Free Estimation for Spatiotemporal Hawkes processes with missing data and application to predictive policing
by: Das, Pramit, et al.
Published: (2025)

A Bayesian Multisource Fusion Model for Spatiotemporal PM2.5 in an Urban Setting
by: Riley, Abi I., et al.
Published: (2025)

Hybrid$^2$ Neural ODE Causal Modeling and an Application to Glycemic Response
by: Zou, Bob Junyi, et al.
Published: (2024)

Scalable Decisions using a Bayesian Decision-Theoretic Approach
by: Ng, Hoiyi, et al.
Published: (2026)

Scalable Bayesian Semiparametric Additive Regression Models For Microbiome Studies
by: Chen, Tinghua, et al.
Published: (2024)

Sample Efficient Bayesian Learning of Causal Graphs from Interventions
by: Zhou, Zihan, et al.
Published: (2024)