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Found 4 papers, 1 papers with code
NeoNeXt: Novel neural network operator and architecture based on the patch-wise matrix multiplications
Most of the computer vision architectures nowadays are built upon the well-known foundation operations: fully-connected layers, convolutions and multi-head self-attention blocks.
Neural Tangent Kernel: A Survey
A seminal work [Jacot et al., 2018] demonstrated that training a neural network under specific parameterization is equivalent to performing a particular kernel method as width goes to infinity.
ISyNet: Convolutional Neural Networks design for AI accelerator
To address this problem we propose a measure of hardware efficiency of neural architecture search space - matrix efficiency measure (MEM); a search space comprising of hardware-efficient operations; a latency-aware scaling method; and ISyNet - a set of architectures designed to be fast on the specialized neural processing unit (NPU) hardware and accurate at the same time.
Ranked #20 on
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on ImageNet
Tensor Yard: One-Shot Algorithm of Hardware-Friendly Tensor-Train Decomposition for Convolutional Neural Networks
Nowadays Deep Learning became widely used in many economic, technical and scientific areas of human interest.
