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BayesWatch / deep-kernel-transfer

Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
https://arxiv.org/abs/1910.05199
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whats the role of DKT? How Bayesian is being used in this paper (need under the hood explanation) and how bayesian and DKT are complimenting each other.. #18

Closed Shantan243 closed 1 year ago

Shantan243 commented 2 years ago

Hi, The paper has not explained details of how DKT is creating the difference except in metrics which shows experiement results - Need how DKT is identified as the influencer/factor, what is the role/objective of DKT. Also in papaer, we see Baseline and Baseline++ models , what are these? Could you please give more details/explanations of these Baseline/Baseline++

mpatacchiola commented 2 years ago

Hi @Shantan243

The paper has not explained details of how DKT is creating the difference except in metrics which shows experiement results - Need how DKT is identified as the influencer/factor, what is the role/objective of DKT.

I am not sure what you mean here, can you reformulate the question?

Also in papaer, we see Baseline and Baseline++ models , what are these? Could you please give more details/explanations of these Baseline/Baseline++

Those baselines have been proposed by Chen et al. (2019). They are briefly discussed in the paper (Section 4, Related Work). They use a pretrained backbone that is fine-tuned on a task. Give a look at Chen et al. (2019) for more details.

mpatacchiola commented 1 year ago

Closed for inactivity.