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Group by: Date | Item Type Number of items: 6. 2021Nüsken, N. and Renger, M. (2021) Stein Variational Gradient Descent: many-particle and long-time asymptotics. arXive . pp. 1-25. (Unpublished) 2020Nüsken, N. and Richter, L. (2020) Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space. SFB 1114 Preprint in arXiv . pp. 1-40. (Submitted) 2019Garbuno Inigo, A. and Nüsken, N. and Reich, S. (2019) Affine invariant interacting Langevin dynamics for Bayesian inference. SFB 1114 Preprint in arXiv:1912.02859 . pp. 1-29. (Unpublished) Duncan, A. and Nüsken, N. and Szpruch, L. (2019) On the geometry of Stein variational gradient descent. SFB 1114 Preprint in arXiv:1912.00894 . (Unpublished) Nüsken, N. and Reich, S. (2019) Note on Interacting Langevin Diffusions: Gradient Structure and Ensemble Kalman Sampler by Garbuno-Inigo, Hoffmann, Li and Stuart. arXive . pp. 1-6. (Submitted) Nüsken, N. and Reich, S. and Rozdeba, P.J. (2019) State and parameter estimation from observed signal increments. Entropy, 21 (5). -505. ISSN 1099-4300 |
