González-González, Pablo

24 files · 776 KB · npz

Vectorial representations for common image datasets: CIFAR10, CIFAR100, CIFAR100coarse MNIST, FashionMNIST SVHN Extracted using the scripts in this repo, where more details of the extraction can be consulted. The embeddings are provided in different modalities: features: the next-to-last representation of the network logits: the pre-softmax values predictions: the post-softmax values (posterior probabilities) targets: the true labels Each file is stored in format npz (dictionary-like) and contains the numpy representations for the keys "train", "val", and "test" partitions for each dataset. The "train" partition was used to train the corresponding neural model, "val" was used for training monitoring, and "test" was not used during training. The name of the file uses the format <dataset>_<neural-model>_<modality>.npz; for example: "svhn_resnet18_logits.npz". See reference list for publications related to each dataset.

Cai

12 files · 8.0 MB · npy