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inspire-group/hydra

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View on GitHub↗
91 estrellas·25 forks·Python·3 vistasvsehwag.github.io/hydra↗

Hydra

Repository with code to reproduce the results and checkpoints for compressed networks in our paper on novel pruning techniques with robust training. This repository supports all four robust training objectives: iterative adversarial training, randomized smoothing, MixTrain, and CROWN-IBP.

Features

  • Weight Pruning - Pruning techniques for adversarially robust neural networks.

Historial de estrellas

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Ver las 30 alternativas a Hydra→

Preguntas frecuentes

¿Qué hace inspire-group/hydra?

Repository with code to reproduce the results and checkpoints for compressed networks in our paper on novel pruning techniques with robust training. This repository supports all four robust training objectives: iterative adversarial training, randomized smoothing, MixTrain, and CROWN-IBP.

¿Cuáles son las características principales de inspire-group/hydra?

Las características principales de inspire-group/hydra son: Weight Pruning.

¿Qué alternativas de código abierto existen para inspire-group/hydra?

Las alternativas de código abierto para inspire-group/hydra incluyen: tencent/pocketflow — PocketFlow is an integrated toolkit for deep learning model compression, distributed training, and mobile format… chrundle/biprop — This method identifies a binary weight or binary weight and activation subnetwork within a randomly initialized… dchiji-ntt/iterand — by Daiki Chijiwa\*, Shin’ya Yamaguchi, Yasutoshi Ida, Kenji Umakoshi, Tomohiro Inoue. dem123456789/pruning-deep-neural-networks-from-a-sparsity-perspective — [ICLR 2023] Pruning Deep Neural Networks from a Sparsity Perspective. densoitlab/bitprune — This is the official repo for ICLR 2023 Paper "Bit-Pruning: A Sparse Multiplication-Less Dot-Product" Yusuke Sekikawa… boone891214/sanity-check-lth — Sample code use for NeurIPS 2021 paper: Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the…