Efficiently sampling functions from Gaussian process posteriors
Authors: James Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Deisenroth
ICML 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In a series of experiments designed to test competing sampling schemes statistical properties and practical ramifications, we demonstrate how decoupled sample paths accurately represent Gaussian process posteriors at a fraction of the usual cost. |
| Researcher Affiliation | Academia | 1Imperial College London 2St. Petersburg State University 3St. Petersburg Department of Steklov Mathematical Institute of Russian Academy of Sciences 4University College London. |
| Pseudocode | No | The paper does not contain explicit pseudocode blocks or algorithms labeled as such. |
| Open Source Code | Yes | 4Code: https://github.com/j-wilson/GPflowSampling |
| Open Datasets | No | The paper mentions varying amounts of "training data n" and functions drawn from "known GP priors" but does not specify a named public dataset or provide access information for a training dataset. |
| Dataset Splits | No | The paper does not explicitly provide details about training/validation/test dataset splits, only mentioning training and test locations. |
| Hardware Specification | No | The paper does not explicitly mention specific hardware specifications such as GPU or CPU models used for experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers. |
| Experiment Setup | Yes | Across trials, we varied both the dimensionality d of search spaces X = [0, 1]d and the number of initial basis functions ℓ. We set κ = d, but this choice was not found to greatly influence results. The total number of basis functions allocated to weight-space and decoupled samplers was again matched, so that b = m + ℓ. [...] Results using ℓ {1024, 4096, 16384} initial bases correspond with {light, medium, dark} tones and { , , } markers. |