Recurrent Neural Networks (RNN) and Hidden Markov Models (HMM) are popular models for processing sequential data and have found many applications such as speech

Neural Computing: New Challenges and Perspectives for the New Millennium. Both hidden Markov models (HMMs) and recurrent neural networks (RNNs) have been applied to …

隐状态的表示: hmm是onehot, RNN是分布表示，RNN的表示能力强很多，或者说在面对高维度时，表示效率更高。类似nlp里，对单个token的表示，一种是onehot, 一种是word vector 。

2018年12月21日 · One way to avoid frame-based human annotation is the use of action order information to learn the respective action classes. In this context, we propose a hierarchical …

2019年12月1日 · Recurrent Neural Networks (RNN) and Hidden Markov Models (HMM) are popular models for processing sequential data and have found many applications such as …

We finally discuss about the modeling power of the HMM and RNN submodels, via their associated observations pdf: some observations pdf can be modeled by a RNN, but not by an …

2017年10月26日 · This paper provides an extended comparison of two temporal models for gesture recognition, namely Hybrid Neural Network-Hidden Markov Models (NN-HMM) and …

2024年4月20日 · 回路高速公路网络 （RHN）的核心思想是在循环神经网络（RNN）中引入了“门控”机制，这种机制允许信息在更长时间尺度上自由流动。 与LSTM中的单元状态不同，RHN …

2023年7月15日 · To further explain, this paper introduces a novel and promising hybrid RNN-HMM technique in non-categorical observations such as financial data. It seeks to combine …

Hidden Markov Models (HMMs) are much simpler than Recurrent Neural Networks (RNNs), and rely on strong assumptions which may not always be true. If the assumptions are true then you …