EM Algorithm: An iterative approach to compute maximum likelihood estimates in models with latent variables by alternately estimating hidden data and maximising the likelihood function.

Diego Fiori, CTO at Nebuly, implemented Hinton's FF algorithm and discussed his results on Twitter: Hinton’s paper proposed 2 different Forward-Forward algorithms, which I called Base and Recurrent.

C. Bracken, B. Rajagopalan, & E. Zagona (2014). “A Hidden Markov Model Combined with Climate Indices for Multi-decadal Streamflow Simulation,” Water Resources Research, 50, 7836-7846. Abstract: ...

We study Markov regime-switching Gaussian autoregressive models that capture temporal heterogeneity exhibited by time series data. Constructing a Markov regime-switching model requires making several ...