22 datasets found

MAPLE-Edge: A Runtime Latency Predictor for Edge Devices

Human pose estimation has achieved significant progress in recent years. However, most of the recent methods focus on improving accuracy using complicated models and ignoring...

The dataset used in this paper is a production-scale on-device natural language understanding model.

The NASBench-101 dataset is a large-scale benchmark for neural architecture search. It contains nearly 423K unique convolutional neural network architectures with diverse...

ArchExplorer is a visual analysis method for understanding a neural architecture space and summarizing design principles.

The dataset used in the paper is NAS-Bench-301 and AlphaNet. NAS-Bench-301 is a surrogate NAS benchmark built via deep ensembles and modeling uncertainty, which provides...

The proposed Siamese-Predictor using EFM to fuse prior knowledge - Estimation Code. The proposed Estimation Code and accuracy of architectures are highly correlated based on our...

The proposed Siamese-Predictor using EFM to fuse prior knowledge - Estimation Code. The proposed Estimation Code and accuracy of architectures are highly correlated based on our...

The proposed Siamese-Predictor using EFM to fuse prior knowledge - Estimation Code. The proposed Estimation Code and accuracy of architectures are highly correlated based on our...

The proposed Siamese-Predictor using EFM to fuse prior knowledge - Estimation Code. The proposed Estimation Code and accuracy of architectures are highly correlated based on our...

The proposed Siamese-Predictor using EFM to fuse prior knowledge - Estimation Code. The proposed Estimation Code and accuracy of architectures are highly correlated based on our...

Structural re-parameterization technology provides a new idea to improve the performance of traditional convolutional networks.

The dataset used in the paper to test the proposed Decomposable Winograd Method (DWM) for convolution acceleration.

The dataset used in the paper is NAS-Bench-101, a benchmark for neural architecture search.

The dataset used in the paper is ENAS Macro, a search space for neural architecture search.

The dataset used in the paper is RandWire, a randomly wired neural network search space.

Multi-conditioned Graph Diffusion for Neural Architecture Search

This paper presents a novel framework for data-free neural architecture search (NAS) without access to the original data.

Progressive Neural Architecture Search

Designing Network Design Spaces