3 papers
stat.ML2019
Efficient structure learning with automatic sparsity selection for causal graph processes
Théophile Griveau-Billion, Ben Calderhead
We propose a novel algorithm for efficiently computing a sparse directed adjacency matrix from a group of time series following a causal graph process. Our solution is scalable for…
q-fin.CP2019
A Dynamic Bayesian Model for Interpretable Decompositions of Market Behaviour
Théophile Griveau-Billion, Ben Calderhead
We propose a heterogeneous simultaneous graphical dynamic linear model (H-SGDLM), which extends the standard SGDLM framework to incorporate a heterogeneous autoregressive realised…
math.ST2018
Quasi Markov Chain Monte Carlo Methods
Tobias Schwedes, Ben Calderhead
Quasi-Monte Carlo (QMC) methods for estimating integrals are attractive since the resulting estimators typically converge at a faster rate than pseudo-random Monte Carlo. However,…