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Iuliia Pliushch

2 accepted papers

2022

When Deep Classifiers Agree: Analyzing Correlations between Learning Order and Image Statistics

ECCV 2022poster

"Although a plethora of architectural variants for deep classification has been introduced over time, recent works have found empirical evidence towards similarities in their training process. It has been hypothesized that neural networks converge not only to similar representations, but also exhibi…

2021

A Procedural World Generation Framework for Systematic Evaluation of Continual Learning

NeurIPS 2021poster

Several families of continual learning techniques have been proposed to alleviate catastrophic interference in deep neural network training on non-stationary data. However, a comprehensive comparison and analysis of limitations remains largely open due to the inaccessibility to suitable datasets. Em…

Cited by 9SourceScholar