The code base for project Probabilistic Transformer, a model of contextual word representation from a syntactic and probabilistic perspective. The paper " ...

Nov 26, 2023 · In this work, we propose a new model of contextual word representation, not from a neural perspective, but from a purely syntactic and probabilistic ...

Thanks! Probabilistic Transformer: A Probabilistic Dependency Model for Contextual Word Representation wuhy1@shanghaitech.edu.cn.

Sep 25, 2023 · Here we propose the Generative Molecular Transformer (GMTransformer), a probabilistic neural network model for generative design of molecules.

Mar 6, 2024 · We propose the Transformer-Representation Neural Topic Model (TNTM), which combines the benefits of topic representations in transformer-based ...

This paper proposes a Transformer-based probabilistic residential net load forecasting method that utilizes quantile regression to quantify uncertainty in ...

Dec 1, 2022 · The Transformers library comes with a vanilla probabilistic time series Transformer model, simply called the Time Series Transformer. In ...

Oct 31, 2022 · This paper introduced ProbTransformer, which is a transformer based generative model. By adding a probabilistic architecture to the original ...

In this paper, we propose deep probabilistic methods that combine state-space models (SSMs) with transformer architectures. In contrast to previously proposed ...

This paper introduces a probabilis- tic model named Uncertainty-Guided Probabilistic Trans- former (UGPT) for complex action recognition. The self- attention ...