Semantic uncertainty intervals for disentangled latent spaces
Authors: Swami Sankaranarayanan, Anastasios Angelopoulos, Stephen Bates, Yaniv Romano, Phillip Isola
NeurIPS 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 3 Experiments3.1 Dataset descriptions3.2 Experimental setup3.3 Findings |
| Researcher Affiliation | Academia | 1MIT 2University of California, Berkeley 3Technion Israel Institute of Technology |
| Pseudocode | Yes | Algorithm 1 Quantile GAN encoder training |
| Open Source Code | No | The code will be released in the near future. |
| Open Datasets | Yes | FFHQ We use the Style GAN framework pretrained using the Flickr-Faces-HQ (FFHQ) dataset [25]. FFHQ is a publicly available dataset consisting of 70,000 high-quality images at 1024 1024 resolution. ... Celeb A-HQ We use the Celeb A-HQ dataset [23]... CLEVR dataset [22]. |
| Dataset Splits | Yes | We generate 100k samples per model and generate a random 80-10-10 split for training, calibration and validation. |
| Hardware Specification | No | The paper's self-assessment in section 3d explicitly states: "Did you include the total amount of compute and the type of resources used (e.g., type of GPUs, internal cluster, or cloud provider)? [No]" |
| Software Dependencies | No | The paper mentions software like Style GAN2, ResNet-50, Ranger optimizer, VGG network, but does not provide specific version numbers for these software dependencies. |
| Experiment Setup | Yes | The hyperparameter weights (Eq 8) are set to c1 = c2 = 10.0. ... a flat learning rate of 0.001 for all our experiments. ... The risk level α and the user-specified error threshold δ are fixed to 0.1, unless specified otherwise. ... For the image super-resolution training, we augment the input dataset by using different levels of downsampled inputs, i.e., we take the raw input and apply a random downsampling factor from {1, 4, 8, 16, 32} and resize it to the original dimensions. |