Search results

• 2024

  Coherent set identification via direct low rank maximum likelihood estimation

  Polzin, R., Nusken, N., Klebanov, I. & Koltai, P., 14 Sept 2024, (Accepted/In press) In: JOURNAL OF NONLINEAR SCIENCE.

  Research output: Contribution to journal › Article › peer-review

  File

  • Bounds 100%
  • Factorization 100%
  • Bayesian Model 100%
  • Maximum Likelihood 100%
  • Matrix 50%
  12 Downloads (Pure)

• From continuous-time formulations to discretization schemes: tensor trains and robust regression for BSDEs and parabolic PDEs

  Richter, L., Sallandt, L. & Nusken, N., Jun 2024, In: JOURNAL OF MACHINE LEARNING RESEARCH.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Parabolic 100%
  • Tensor 100%
  • Discretization 100%
  • Robust Regression 100%
  • Discretization Scheme 100%
  21 Downloads (Pure)
• 2023

  Interpolating Between BSDEs and PINNs: Deep Learning for Elliptic and Parabolic Boundary Value Problems

  Nusken, N. & Richter, L., Mar 2023, In: Journal of Machine Learning. 2, 1, p. 31-64

  Research output: Contribution to journal › Article › peer-review

  File

  • Boundary Value 100%
  • Stochastic Differential 100%
  • Physics Informed Neural Network 100%
  • Stochastic Differential Equation 100%
  • Parabolic 100%
  45 Downloads (Pure)

• On the geometry of Stein variational gradient descent

  Duncan, A., Szpruch, L. & Nusken, N., 1 Jan 2023, In: JOURNAL OF MACHINE LEARNING RESEARCH. 24, 56, p. 1-39 39 p.

  Research output: Contribution to journal › Article › peer-review

  File

  • Geometry 100%
  • Probability Theory 50%
  • Probability Distribution 50%
  • Positive Definite 50%
  • Bayesian Inference 50%
  16 Downloads (Pure)

• Rough McKean–Vlasov dynamics for robust ensemble Kalman filtering

  Coghi, M., Nilssen, T., Nusken, N. & Reich, S., 13 Dec 2023, In: The Annals of Applied Probability. 33, 6B, p. 5693-5752 60 p.

  Research output: Contribution to journal › Article › peer-review

  File

  • Kalman Filtering 100%
  • Rough Paths 100%
  • Number 25%
  • Dynamical Model 25%
  • Interacting Particle Systems 25%
  6 Downloads (Pure)

• Stein variational gradient descent: Many-particle and long-time asymptotics

  Nusken, N. & Renger, M., 1 Sept 2023, In: Foundations of Data Science. 5, 3, p. 286-320

  Research output: Contribution to journal › Article › peer-review

  File

  • Asymptotics 100%
  • Geometry 50%
  • Bayesian 50%
  • Measures 50%
  • Large Deviations 50%
  3 Citations (Scopus)

  6 Downloads (Pure)
• 2022

  Bayesian learning via neural Schrödinger–Föllmer flows

  Vargas, F., Ovsianas, A., Fernandes, D., Girolami, M., Lawrence, N. & Nusken, N., 23 Nov 2022, In: STATISTICS AND COMPUTING. 33

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Bayesian 100%
  • Bayesian Learning 100%
  • Stochastic Control 100%
  • Control 66%
  • Large Data Set 50%
  28 Downloads (Pure)