ML Collective’s ICML Paper: A Probabilistic Interpretation of Transformers

In the new paper A Probabilistic Interpretation of Transformers, ML Collective researcher Alexander Shim provides a probabilistic explanation of transformers' exponential dot product attention and contrastive learning based on distributions of the exponential family.

ai artificial intelligence deep-neural-networks icml interpretation machine learning machine learning & data science ml paper probability theory research technology transformers