LSTM

AI Research

Explaining the Paper: Hopfield Networks is All You Need

Yannic Kilcher explains the paper “Hopfield Networks is All You Need.” Hopfield Networks are one of the classic models of biological memory networks. This paper generalizes modern Hopfield Networks to continuous states and shows that the corresponding update rule is equal to the attention mechanism used in modern Transformers. It further analyzes a pre-trained BERT […]

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AI Machine Learning

Object-Centric Learning with Slot Attention

Visual scenes are often comprised of sets of independent objects. Yet, current vision models make no assumptions about the nature of the pictures they look at. Yannic Kilcher explore a paper on object-centric learning. By imposing an objectness prior, this paper a module that is able to recognize permutation-invariant sets of objects from pixels in […]

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AI Neural Networks

Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM)

Brandon Rohrer explains Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) in this informative video.

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