9 citations · 11 across the 4 of their papers we have counts for
5 papers
Projection Filtering with Observed State Increments with Applications in Continuous-Time Circular Filtering
Anna Kutschireiter, Luke Rast, Jan Drugowitsch
Angular path integration is the ability of a system to estimate its own heading direction from potentially noisy angular velocity (or increment) observations. Non-probabilistic alg…
Asymptotically exact unweighted particle filter for manifold-valued hidden states and point process observations
Simone Carlo Surace, Anna Kutschireiter, Jean-Pascal Pfister
The filtering of a Markov diffusion process on a manifold from counting process observations leads to `large' changes in the conditional distribution upon an observed event, corres…
The Hitchhiker's Guide to Nonlinear Filtering
Anna Kutschireiter, Simone Carlo Surace, Jean-Pascal Pfister
Nonlinear filtering is the problem of online estimation of a dynamic hidden variable from incoming data and has vast applications in different fields, ranging from engineering, mac…
Particle-filtering approaches for nonlinear Bayesian decoding of neuronal spike trains
Anna Kutschireiter, Jean-Pascal Pfister
The number of neurons that can be simultaneously recorded doubles every seven years. This ever increasing number of recorded neurons opens up the possibility to address new questio…
How to avoid the curse of dimensionality: scalability of particle filters with and without importance weights
Simone Carlo Surace, Anna Kutschireiter, Jean-Pascal Pfister
Particle filters are a popular and flexible class of numerical algorithms to solve a large class of nonlinear filtering problems. However, standard particle filters with importance…