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Grzegorz Rypeść

3 accepted papers

2024

Divide and not forget: Ensemble of selectively trained experts in Continual Learning

ICLR 2024poster

Class-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained…

2024

Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning

NeurIPS 2024poster

Exemplar-Free Class Incremental Learning (EFCIL) tackles the problem of training a model on a sequence of tasks without access to past data. Existing state-of-the-art methods represent classes as Gaussian distributions in the feature extractor's latent space, enabling Bayes classification or trainin…

2023

Active Visual Exploration Based on Attention-Map Entropy

IJCAI 2023poster

Active visual exploration addresses the issue of limited sensor capabilities in real-world scenarios, where successive observations are actively chosen based on the environment. To tackle this problem, we introduce a new technique called Attention-Map Entropy (AME). It leverages the internal uncerta…