| Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception A Kutschireiter, SC Surace, H Sprekeler, JP Pfister Scientific reports 7 (1), 8722, 2017 | 59 | 2017 |
| How to avoid the curse of dimensionality: Scalability of particle filters with and without importance weights SC Surace, A Kutschireiter, JP Pfister SIAM review 61 (1), 79-91, 2019 | 50 | 2019 |
| The Hitchhikers Guide to Nonlinear Filtering A Kutschireiter, SC Surace, JP Pfister Journal of Mathematical Psychology, 2020 | 22 | 2020 |
| Bayesian inference in ring attractor networks A Kutschireiter, MA Basnak, RI Wilson, J Drugowitsch Proceedings of the National Academy of Sciences 120 (9), e2210622120, 2023 | 17 | 2023 |
| Projection filtering with observed state increments with applications in continuous-time circular filtering A Kutschireiter, L Rast, J Drugowitsch IEEE Transactions on Signal Processing 70, 686-700, 2022 | 11* | 2022 |
| Approximate nonlinear filtering with a recurrent neural network A Kutschireiter, SC Surace, H Sprekeler, JP Pfister BMC Neuroscience 16, 1-2, 2015 | 4 | 2015 |
| A Bayesian perspective on the ring attractor for heading-direction tracking in the Drosophila central complex A Kutschireiter, MA Basnak, RI Wilson, J Drugowitsch bioRxiv, 2021 | 3 | 2021 |
| Asymptotically exact unweighted particle filter for manifold-valued hidden states and point process observations SC Surace, A Kutschireiter, JP Pfister IEEE Control Systems Letters 4 (2), 480-485, 2019 | 3 | 2019 |
| Particle-filtering approaches for nonlinear Bayesian decoding of neuronal spike trains A Kutschireiter, JP Pfister arXiv preprint arXiv:1804.09739, 2018 | 2 | 2018 |
| Nonlinear filtering in neuroscience: theory and application A Kutschireiter University of Zurich, 2018 | 2 | 2018 |
