The code base for project Probabilistic Transformer, a model of contextual word representation from a syntactic and probabilistic perspective. The paper " ...
In this paper, we propose deep probabilistic methods that combine state-space models (SSMs) with transformer architectures. In contrast to previously proposed ...
What is a Probabilistic Transformer? Part 1. The Probabilistic Transformer. • A probabilistic model… • …for contextual word representation.
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Oct 15, 2020 · Abstract:We show that Transformers are Maximum Posterior Probability estimators for Mixtures of Gaussian Models. This brings a probabilistic ...
Dec 1, 2022 · Forecasting involves getting data from the test instance sampler, which will sample the very last context_length sized window of values from ...
Nov 26, 2023 · When used as an encoder, a transformer produces contextual representation of words in the input sentence. In this work, we propose a new model ...
Oct 31, 2022 · Enhancing Transformers with hierarchical latent distributions to model ambiguities and distributions for RNA folding and Molecular Design.
This paper introduces a probabilis- tic model named Uncertainty-Guided Probabilistic Trans- former (UGPT) for complex action recognition. The self- attention ...
An interpretable sparse self-attention mechanism is adopted in InterFormer to model the long-term dependencies of all input time steps. The self-attention ...
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