SNAIL

2000년 도입 · 논문 11편에서 사용

The Simple Neural Attention Meta-Learner, or SNAIL, combines the benefits of temporal convolutions and attention to solve meta-learning tasks. They introduce positional dependence through temporal convolutions to make the model applicable to reinforcement tasks - where the observations, actions, and rewards are intrinsically sequential. They also introduce attention in order to provide pinpoint access over an infinitely large context. SNAIL is constructing by combining the two: we use temporal convolutions to produce the context over which we use a causal attention operation.

출처: A Simple Neural Attentive Meta-Learner

소개 논문: A Simple Neural Attentive Meta-Learner