Research map / Probabilistic and scientific modeling / Uncertainty and Gaussian processes
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference (NeurIPS 2017 · similarity 0.93)
- Scaled Least Squares Estimator for GLMs in Large-Scale Problems (NeurIPS 2016 · similarity 0.88)
- Least squares variational inference (NeurIPS 2025 · similarity 0.85)
- Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models (NeurIPS 2024 · similarity 0.84)
- Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project (NeurIPS 2025 · similarity 0.84)
- Asymptotically Log-Optimal Bayes-Assisted Confidence Sequences for Bounded Means (NeurIPS 2026 · similarity 0.83)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.