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Found 7 papers, 2 papers with code
Nonlinear Permuted Granger Causality
Granger causal inference is a contentious but widespread method used in fields ranging from economics to neuroscience.
Change Point Detection with Conceptors
Offline change point detection retrospectively locates change points in a time series.
Bridging the Usability Gap: Theoretical and Methodological Advances for Spectral Learning of Hidden Markov Models
In this paper, we (1) provide an asymptotic distribution for the approximate error of the likelihood estimated by SHMM, (2) propose a novel algorithm called projected SHMM (PSHMM) that mitigates the problem of error propagation, and (3) develop online learning variants of both SHMM and PSHMM that accommodate potential nonstationarity.
Trees in transformers: a theoretical analysis of the Transformer's ability to represent trees
To date, there are no theoretical analyses of the Transformer's ability to capture tree structures.
When black box algorithms are (not) appropriate: a principled prediction-problem ontology
In this paper, we introduce the term "outcome reasoning" to refer to this form of reasoning.
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Multiscale Hidden Markov Models For Covariance Prediction
This paper presents a novel variant of hierarchical hidden Markov models (HMMs), the multiscale hidden Markov model (MSHMM), and an associated spectral estimation and prediction scheme that is consistent, finds global optima, and is computationally efficient.
