Efficient Neural Network

72 papers with code • 0 benchmarks • 0 datasets

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Use these libraries to find Efficient Neural Network models and implementations

Most implemented papers

ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

PaddlePaddle/PaddleSeg 7 Jun 2016

The ability to perform pixel-wise semantic segmentation in real-time is of paramount importance in mobile applications.

Efficient Neural Network Robustness Certification with General Activation Functions

huanzhang12/CROWN-Robustness-Certification NeurIPS 2018

Finding minimum distortion of adversarial examples and thus certifying robustness in neural network classifiers for given data points is known to be a challenging problem.

Network Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures

BenWhetton/keras-surgeon 12 Jul 2016

We alternate the pruning and retraining to further reduce zero activations in a network.

MobileOne: An Improved One millisecond Mobile Backbone

rwightman/pytorch-image-models CVPR 2023

Furthermore, we show that our model generalizes to multiple tasks - image classification, object detection, and semantic segmentation with significant improvements in latency and accuracy as compared to existing efficient architectures when deployed on a mobile device.

vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design

shriramsb/vdnn-plus-plus 25 Feb 2016

The most widely used machine learning frameworks require users to carefully tune their memory usage so that the deep neural network (DNN) fits into the DRAM capacity of a GPU.

Sudo rm -rf: Efficient Networks for Universal Audio Source Separation

etzinis/sudo_rm_rf 14 Jul 2020

In this paper, we present an efficient neural network for end-to-end general purpose audio source separation.

Deep learning observables in computational fluid dynamics

kjetil-lye/learning_airfoils 7 Mar 2019

Under the assumption that the underlying neural networks generalize well, we prove that the deep learning MC and QMC algorithms are guaranteed to be faster than the baseline (quasi-) Monte Carlo methods.

Compute and memory efficient universal sound source separation

etzinis/sudo_rm_rf 3 Mar 2021

Recent progress in audio source separation lead by deep learning has enabled many neural network models to provide robust solutions to this fundamental estimation problem.

SkyNet: a Hardware-Efficient Method for Object Detection and Tracking on Embedded Systems

TomG008/SkyNet 20 Sep 2019

Object detection and tracking are challenging tasks for resource-constrained embedded systems.

LUTNet: Learning FPGA Configurations for Highly Efficient Neural Network Inference

awai54st/LUTNet 24 Oct 2019

Research has shown that deep neural networks contain significant redundancy, and thus that high classification accuracy can be achieved even when weights and activations are quantized down to binary values.