Behavioral Change Point Analysis (BCPA)
The Behavioral Change Point Analysis (BCPA) is a method of identifying hidden shifts in the underlying parameters of a time series, developed specifically to be applied to animal movement data which is irregularly sampled. …

Generalized Additive Models (GAM)
In statistics, a generalized additive model (GAM) is a generalized linear model in which the linear predictor depends linearly on unknown smooth functions of some predictor variables, and interest focuses on inference about these smooth functions. GAMs were originally developed by Trevor Hastie and Robert Tibshirani to blend properties of generalized linear models with additive models.
https://…-additive-part-i-background-and-rationale
GAM: The Predictive Modeling Silver Bullet …

Dilated Recurrent Neural Network (DILATEDRNN)
Notoriously, learning with recurrent neural networks (RNNs) on long sequences is a difficult task. There are three major challenges: 1) extracting complex dependencies, 2) vanishing and exploding gradients, and 3) efficient parallelization. In this paper, we introduce a simple yet effective RNN connection structure, the DILATEDRNN, which simultaneously tackles all these challenges. The proposed architecture is characterized by multi-resolution dilated recurrent skip connections and can be combined flexibly with different RNN cells. Moreover, the DILATEDRNN reduces the number of parameters and enhances training efficiency significantly, while matching state-of-the-art performance (even with Vanilla RNN cells) in tasks involving very long-term dependencies. To provide a theory-based quantification of the architecture’s advantages, we introduce a memory capacity measure – the mean recurrent length, which is more suitable for RNNs with long skip connections than existing measures. We rigorously prove the advantages of the DILATEDRNN over other recurrent neural architectures. …