Solving high-dimensional Hamilton–Jacobi–Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space von Nüsken, Nikolas, Richter, Lorenz

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HYPOCOERCIVITY OF PIECEWISE DETERMINISTIC MARKOV PROCESS-MONTE CARLO von Andrieu, Christophe, Durmus, Alain, Nüsken, Nikolas, Roussel, Julien

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State and Parameter Estimation from Observed Signal Increments von Nüsken, Nikolas, Reich, Sebastian, Rozdeba, Paul J.

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Bayesian learning via neural Schrödinger–Föllmer flows von Vargas, Francisco, Ovsianas, Andrius, Fernandes, David, Girolami, Mark, Lawrence, Neil D., Nüsken, Nikolas

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Coherent Set Identification Via Direct Low Rank Maximum Likelihood Estimation von Polzin, Robert M., Klebanov, Ilja, Nüsken, Nikolas, Koltai, Péter

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Affine Invariant Interacting Langevin Dynamics for Bayesian Inference von Garbuno-Inigo, Alfredo, Nüsken, Nikolas, Reich, Sebastian

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Rough McKean–Vlasov dynamics for robust ensemble Kalman filtering von Coghi, Michele, Nilssen, Torstein, Nüsken, Nikolas, Reich, Sebastian

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Stein transport for Bayesian inference von Nüsken, Nikolas

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Topics in sampling schemes based on Markov processes von Nüsken, Nikolas

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Stein transport for Bayesian inference von Nüsken, Nikolas

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Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems von Nüsken, Nikolas, Richter, Lorenz

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Solving high-dimensional Hamilton–Jacobi–Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space von Nüsken, Nikolas, Richter, Lorenz

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From continuous-time formulations to discretization schemes: tensor trains and robust regression for BSDEs and parabolic PDEs von Richter, Lorenz, Sallandt, Leon, Nüsken, Nikolas

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Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space von Nüsken, Nikolas, Richter, Lorenz

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Note on Interacting Langevin Diffusions: Gradient Structure and Ensemble Kalman Sampler by Garbuno-Inigo, Hoffmann, Li and Stuart von Nüsken, Nikolas, Reich, Sebastian

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Skew-symmetric schemes for stochastic differential equations with non-Lipschitz drift: an unadjusted Barker algorithm von Livingstone, Samuel, Nüsken, Nikolas, Vasdekis, Giorgos, Zhang, Rui-Yang

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Coherent Set Identification Via Direct Low Rank Maximum Likelihood Estimation von Polzin, Robert M, Klebanov, Ilja, Nüsken, Nikolas, Koltai, Péter

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Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space von Nüsken, Nikolas, Richter, Lorenz

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Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems von Nüsken, Nikolas, Richter, Lorenz

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Coherent set identification via direct low rank maximum likelihood estimation von Polzin, Robert, Klebanov, Ilja, Nüsken, Nikolas, Koltai, Péter

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