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Search results for python sparsity

34 search results found

Sparseml ⭐ 1,910

Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models

Neural Compressor ⭐ 1,773

SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime

Paddleslim ⭐ 1,486

PaddleSlim is an open-source library for deep model compression and architecture search.

Model Optimization ⭐ 1,445

A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.

Neural Network Compression Framework for enhanced OpenVINO™ inference

Network Slimming ⭐ 499

Network Slimming (Pytorch) (ICCV 2017)

Sparse Optimisation Research Code

[NeurIPS'23] H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models.

Sparse Structured Attention ⭐ 190

Sparse and structured neural attention mechanisms

Sparse Evolutionary Artificial Neural Networks ⭐ 187

Always sparse. Never dense. But never say never. A Sparse Training repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).

Selecsls Pytorch ⭐ 165

Reference ImageNet implementation of SelecSLS CNN architecture proposed in the SIGGRAPH 2020 paper "XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera". The repository also includes code for pruning the model based on implicit sparsity emerging from adaptive gradient descent methods, as detailed in the CVPR 2019 paper "On implicit filter level sparsity in Convolutional Neural Networks".

Iss Rnns ⭐ 62

Sparse Recurrent Neural Networks -- Pruning Connections and Hidden Sizes (TensorFlow)

Soft Threshold Weight Reparameterization for Learnable Sparsity

[ICML 2023] UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers.

In Time Over Parameterization ⭐ 42

[ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy

Official Pytorch Implementation of "Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity"

A package for AFM image reconstruction and compressed sensing in general

Attention Guided Sparsity ⭐ 25

Attention-Based Guided Structured Sparsity of Deep Neural Networks

Smc Bench ⭐ 21

[ICLR 2023] "Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!" Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, AJAY KUMAR JAISWAL, Zhangyang Wang

Backdoor Lth ⭐ 18

[CVPR 2022] "Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free" by Tianlong Chen*, Zhenyu Zhang*, Yihua Zhang*, Shiyu Chang, Sijia Liu, and Zhangyang Wang

Quickselection ⭐ 15

[Machine Learning Journal (ECML-PKDD 2022 journal track)] Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders

Iterative Soft Shrinkage Sr ⭐ 15

[ICCV2023 Official PyTorch code] for Iterative Soft Shrinkage Learning for Efficient Image Super-Resolution

Sparsity Win Robust Generalization ⭐ 15

[ICLR 2022] "Sparsity Winning Twice: Better Robust Generalization from More Efficient Training" by Tianlong Chen*, Zhenyu Zhang*, Pengjun Wang*, Santosh Balachandra*, Haoyu Ma*, Zehao Wang, Zhangyang Wang

Deltarnn ⭐ 12

Latest PyTorch Implementation of DeltaGRU & DeltaLSTM that Exploits Temporal Sparsity in Sequential Data

Progressive Pruning ⭐ 12

Official pytorch code for "APP: Anytime Progressive Pruning" (DyNN @ ICML, 2022; CLL @ ACML, 2022, SNN @ ICML, 2022 and SlowDNN 2023)

Efficientcof ⭐ 11

A new efficient subspace and K-Means clustering based method to improve Collaborative Filtering

Ssld Face_recognition ⭐ 11

Robust Single Sample Face Recognition by Sparsity-Driven Sub-Dictionary Learning Using Deep Features

Variational Interpretable Concept Embeddings

ScaLed: Improving SEAL by random walks

Torch_topkast ⭐ 6

PyTorch Implementation of TopKAST

Effect Dps Public ⭐ 6

Understanding the effects of data parallelism and sparsity on neural network training

Smooth Convex Kl Nmf ⭐ 5

Repository holding various implementation of specific NMF methods for speaker diarization

Dynamic Sparse Training For Deep Reinforcement Learning ⭐ 5

[IJCAI 2022] "Dynamic Sparse Training for Deep Reinforcement Learning" by Ghada Sokar, Elena Mocanu , Decebal Constantin Mocanu, Mykola Pechenizkiy, and Peter Stone.

Double Win Lth ⭐ 5

[ICML 2022] "Data-Efficient Double-Win Lottery Tickets from Robust Pre-training" by Tianlong Chen, Zhenyu Zhang, Sijia Liu, Yang Zhang, Shiyu Chang, Zhangyang Wang

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