Gradient Estimators for Implicit Models
Authors: Yingzhen Li, Richard E. Turner
ICLR 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The efficacy of the proposed estimator is empirically demonstrated by examples that include gradient-free MCMC, meta-learning for approximate inference and entropy regularised GANs that provide improved sample diversity. |
| Researcher Affiliation | Academia | Yingzhen Li & Richard E. Turner University of Cambridge Cambridge, CB2 1PZ, UK {yl494,ret26}@cam.ac.uk |
| Pseudocode | No | The paper describes methods through text and mathematical equations but does not include any structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | Implementation is released at https://github.com/Yingzhen Li/Stein Grad. |
| Open Datasets | Yes | We take from the UCI repository (Lichman, 2013) six binary classification datasets (australian, breast, crabs, ionosphere, pima, sonar) |
| Dataset Splits | Yes | We use ionosphere as the validation set to tune ζ. The remaining 4 datasets are further split into 40% training subset for simulating samples from the approximate sampler, and 60% test subsets for evaluating the sampler s performance. |
| Hardware Specification | Yes | All the methods are timed on a machine with an NVIDIA Ge Force GTX TITAN X GPU. |
| Software Dependencies | No | The paper mentions using 'Adam optimiser' but does not provide specific software dependencies with version numbers (e.g., Python, PyTorch, TensorFlow versions or specific library versions). |
| Experiment Setup | Yes | For the training task... The step-size ζ is selected as 1e-5... The learning rate is set to 0.001, the number of epochs is set to 500... The minibatch size is set to K = 100. Learning rate is initialised at 0.0002 and decayed by 0.9 every 10 epochs... The selected γ and α values are: for KDE estimator approach γ = 0.3, αγ = 0.05, for score matching estimator approach γ = 0.3, αγ = 0.1, and for Stein approach γ = 0.5 and αγ = 0.3. |