Gradient-Free Kernel Stein Discrepancy
Authors: Matthew Fisher, Chris J. Oates
NeurIPS 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The practical performance of GF-KSD remains to be assessed. Suitable choices for both q and the kernel parameters σ and β are proposed and investigated in Section 3, and practical demonstrations of GF-KSD are presented in Section 4. |
| Researcher Affiliation | Academia | 1Newcastle University, UK 2Alan Turing Institute, UK |
| Pseudocode | No | The paper describes methods using prose and mathematical notation but does not include any pseudocode or algorithm blocks. |
| Open Source Code | Yes | Python code to reproduce the experiments reported below can be downloaded at [blinded]. |
| Open Datasets | Yes | The data analysed are due to Hewitt [1921], and full details are contained in Appendix C.3. |
| Dataset Splits | No | The paper discusses 'sequences (πn)n N' and 'samples (xn)n N' in its experiments, and describes optimization processes, but does not provide explicit training/validation/test dataset splits for reproducibility. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used for running its experiments. |
| Software Dependencies | Yes | In order to obtain independent samples from the posterior for comparison, we utilised Stan [Stan Development Team, 2022]... URL https://mc-stan.org/. R package version 2.21.5. |
| Experiment Setup | Yes | The Laplace approximation was obtained by the use of 48 iterations of the L-BFGS optimisation algorithm... The stochastic optimisation routine used was Adam [Kingma and Ba, 2015] with learning rate 0.001. Due to issues involving exploding gradients due to the q/p term in GF-KSD, we utilised gradient clipping... with the maximum 2-norm value taken to be 30. In the banana experiment, the dimensionality of the hidden units in the underlying autoregressive neural network was taken as 20. |