93 datasets found

The dataset used in this paper is a MobileNetV2 model, which is a type of deep neural network. The dataset is used to evaluate the performance of the proposed heterogeneous system.

The dataset used in this paper is not explicitly described, but it is mentioned that it contains four DAGs representing well-known exposure-outcome relationships in the medical...

The dataset used in the paper is not explicitly described. However, it is mentioned that the authors used a range of datasets, including CIFAR-10, GTSRB, Google Speech Command,...

DeepSynth: Three-dimensional nuclear segmentation of biological images using neural networks trained with synthetic data.

AlexNet for time series classification

Infrasound data classification using neural networks

Quantization is a promising approach for reducing the inference time and memory footprint of neural networks. However, most existing quantization methods require access to the...

The dataset used in the paper is a population of trained NN models, from the model zoo dataset (Sch¨urholt et al., 2022c).

A dataset for exploring the limits of large-scale pre-training.

A smoothly broken power law functional form that accurately models and extrapolates the scaling behaviors of deep neural networks for various architectures and tasks.

Each node is a client in a German bank, while each edge between any two clients represents that they bear similar credit accounts. Here the gender of bank clients is considered...

The COMPAS dataset is a collection of 10,000 records, each containing information about an individual's criminal history and demographic characteristics. The dataset is used for...

Neural STPP is a strong baseline for time series classification.