Time Series

Ensembles for Time Series Forecasting ACML 2014 Learning Time-Varying Coverage Functions NeurIPS 2014 Link Prediction in Graphs with Autoregressive Features JMLR 2014 Metric Learning for Temporal Sequence Alignment NeurIPS 2014 Shaping Social Activity by Incentivizing Users NeurIPS 2014 Variational Gaussian Process State-Space Models NeurIPS 2014 Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC NeurIPS 2013 Dynamic Covariance Models for Multivariate Financial Time Series ICML 2013 Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data ICML 2013 Learning Connections in Financial Time Series ICML 2013 Learning Triggering Kernels for Multi-dimensional Hawkes Processes ICML 2013 Locally Adaptive Bayesian Multivariate Time Series NeurIPS 2013 Mixed LICORS: A Nonparametric Algorithm for Predictive State Reconstruction AISTATS 2013 Multilinear Dynamical Systems for Tensor Time Series NeurIPS 2013 Nonparametric Multi-group Membership Model for Dynamic Networks NeurIPS 2013 Speeding up Permutation Testing in Neuroimaging NeurIPS 2013 The Extended Parameter Filter ICML 2013 Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting NeurIPS 2012 Density-Difference Estimation NeurIPS 2012 Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential _1-Minimization NeurIPS 2012 Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data NeurIPS 2012 Link Prediction in Graphs with Autoregressive Features NeurIPS 2012 Modelling Reciprocating Relationships with Hawkes Processes NeurIPS 2012 Multiplicative Forests for Continuous-Time Processes NeurIPS 2012 Online allocation and homogeneous partitioning for piecewise constant mean-approximation NeurIPS 2012