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GitHub / ksheersagaragrawal / LotteryTicketPruning
Study and Implementation of various neural network pruning techniques. Extending the lottery ticket hypothesis to structured pruning for accelerated training while maintaining uncertainty and accuracy. The focus is on simplifying the model's complexity without sacrificing its overall performance or leading to overfitting.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksheersagaragrawal%2FLotteryTicketPruning
Stars: 0
Forks: 0
Open Issues: 0
License: None
Language: Jupyter Notebook
Repo Size: 153 MB
Dependencies:
7
Created: 9 months ago
Updated: 4 months ago
Last pushed: 4 months ago
Last synced: 4 months ago
Topics: accuracy-analysis, cifar10, expected-caliberation-error, make-moons, mnist-dataset, monte-carlo-drop-out, pruning-algorithms, reliability-diagram, uncertainty-quantification