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365 Days Computer Vision Learning Linkedin Post ⭐ 290

365 Days Computer Vision Learning Linkedin Post

Lottery Ticket Hypothesis In Pytorch ⭐ 209

This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily adapted to any model/dataset.

[ICLR'19] Meta-learning with differentiable closed-form solvers

Variance Networks ⭐ 37

Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019

Neural Persistence ⭐ 14

Code for the paper 'Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology'

Single shot neural network pruning before training the model, based on connection sensitivity

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