Papers with Code 아카이브

Neural Network Compression

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보존된 평가 기록: 4

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/cunningham-lab/cb

The continuous categorical: a novel simplex-valued exponential family

https://github.com/daskol/fewbit

Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction

https://github.com/duggalrahul/REST

REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild

https://github.com/for-ai/TD

Learning Sparse Networks Using Targeted Dropout

https://github.com/huawei-noah/DAFL

Data-Free Learning of Student Networks

https://github.com/huawei-noah/Data-Efficient-Model-Compression

Data-Free Learning of Student Networks

https://github.com/hyang1990/energy_constrained_compression

ECC: Platform-Independent Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model

https://github.com/hyang1990/sparsity_quantization_joint

Automatic Neural Network Compression by Sparsity-Quantization Joint Learning: A Constrained Optimization-based Approach

https://github.com/ihaeyong/pfnr

NeRV: Neural Representations for Videos

https://github.com/ihaeyong/pnr

NeRV: Neural Representations for Videos

https://github.com/jakc4103/DFQ

ZeroQ: A Novel Zero Shot Quantization Framework

https://github.com/kpaupamah/compression-and-regularisation

Quantisation and Pruning for Neural Network Compression and Regularisation

https://github.com/maheshkaran/Nervana-Distiller

Improving Neural Network Quantization without Retraining using Outlier Channel Splitting

https://github.com/mcordier/Papers-Presentation-ML-Reading-Group-

Diversity Networks: Neural Network Compression Using Determinantal Point Processes

https://github.com/musco-ai/musco-pytorch

MUSCO: Multi-Stage Compression of neural networks

https://github.com/musco-ai/musco-tf

MUSCO: Multi-Stage Compression of neural networks

https://github.com/newwhitecheng/compress-all-nn

Differentiable Fine-grained Quantization for Deep Neural Network Compression

https://github.com/nobug-code/Diversity_Networks_CNN_Pytorch

Diversity Networks: Neural Network Compression Using Determinantal Point Processes

https://github.com/ofsoundof/Heterogeneity_Hypothesis

Learning Filter Basis for Convolutional Neural Network Compression

https://github.com/ofsoundof/group_sparsity

Learning Filter Basis for Convolutional Neural Network Compression

https://github.com/ricky40403/GDFQ

ZeroQ: A Novel Zero Shot Quantization Framework

https://github.com/yuchaoli/CC

Towards Compact CNNs via Collaborative Compression

https://github.com/zhanhuijing/ECC_PYCHARM

ECC: Platform-Independent Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.