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Found 4 papers, 2 papers with code
A Gaussian Process-based Streaming Algorithm for Prediction of Time Series With Regimes and Outliers
We introduce LINTEL, which uses the exact filtering distribution at time $t$ with constant-time updates, making the time complexity of the streaming algorithm optimal.
Dynamic Online Ensembles of Basis Expansions
Practical Bayesian learning often requires (1) online inference, (2) dynamic models, and (3) ensembling over multiple different models.
Fusion of Gaussian Processes Predictions with Monte Carlo Sampling
In this paper, we operate within the Bayesian paradigm, relying on Gaussian processes as our models.
Dagma-DCE: Interpretable, Non-Parametric Differentiable Causal Discovery
We introduce Dagma-DCE, an interpretable and model-agnostic scheme for differentiable causal discovery.
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