468 results on '"Jinqiao Duan"'
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2. Maximum principles for nonlocal parabolic Waldenfels operators
3. Particle dynamics and transport enhancement in a confined channel with position-dependent diffusivity
4. Euler-Maruyama Method Based Channel Prediction: An LDE-Net Implementation and Field Evaluation.
5. Symplectic numerical integration for Hamiltonian stochastic differential equations with multiplicative Lévy noise in the sense of Marcus.
6. Small-Noise-Induced Metastable Transition of Periodically Perturbed Systems.
7. Heteroclinic points of multi-dimensional dynamical systems
8. Ergodicity of stochastically forced large scale geophysical flows
9. Random Dynamics of the Stochastic Boussinesq Equations Driven by Lévy Noises
10. Global Mild Solutions and Attractors for Stochastic Viscous Cahn-Hilliard Equation
11. Analysis for a class of stochastic fractional nonlinear Schrödinger equations.
12. Diffusion Model Conditioning on Gaussian Mixture Model and Negative Gaussian Mixture Gradient.
13. Stochastic parameter reduced-order model based on hybrid machine learning approaches.
14. A Stochastic Approach for Parameterizing Unresolved Scales in a System with Memory
15. Multi-task meta label correction for time series prediction.
16. Modulation Analysis of the Stochastic Camassa-Holm Equation with Pure Jump Noise.
17. Early warning via transitions in latent stochastic dynamical systems.
18. Efficient Privacy-Preserving Convolutional Spiking Neural Networks with FHE.
19. Privacy-Preserving Discretized Spiking Neural Networks.
20. Meta contrastive label correction for financial time series.
21. Learning Stochastic Dynamical Systems as an Implicit Regularization with Graph Neural Networks.
22. Early Warning via tipping-preserving latent stochastic dynamical system and meta label correcting.
23. Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker-Planck Equation and Physics-Informed Neural Networks.
24. Homogenization of Dissipative Hamiltonian Systems Under Lévy Fluctuations.
25. Analysis of multiscale methods for stochastic dynamical systems driven by α-stable processes.
26. An end-to-end deep learning approach for extracting stochastic dynamical systems with α-stable Lévy noise.
27. Numerical integration of stochastic contact Hamiltonian systems via stochastic Herglotz variational principle.
28. Auto-SDE: Learning effective reduced dynamics from data-driven stochastic dynamical systems.
29. An Optimal Control Method to Compute the Most Likely Transition Path for Stochastic Dynamical Systems with Jumps.
30. Mean escape time for randomly switching narrow gates in a steady flow.
31. Bifurcation in Mean Phase Portraits for Stochastic Dynamical Systems with Multiplicative Gaussian Noise.
32. Stochastic nonlocal conservation laws on whole space.
33. A novel compact ADI scheme for two-dimensional Riesz space fractional nonlinear reaction-diffusion equations.
34. Most probable dynamics of a genetic regulatory network under stable Lévy noise.
35. Fokker-Planck equation driven by asymmetric Lévy motion.
36. A parameter estimator based on Smoluchowski-Kramers approximation.
37. Extracting stochastic dynamical systems with $α$-stable Lévy noise from data.
38. Time Series Forecasting with Ensembled Stochastic Differential Equations Driven by Lévy Noise.
39. Learning the temporal evolution of multivariate densities via normalizing flows.
40. Data-driven method to learn the most probable transition pathway and stochastic differential equations.
41. The Most Likely Transition Path for a Class of Distribution-Dependent Stochastic Systems.
42. Most Probable Transitions from Metastable to Oscillatory Regimes in a Carbon Cycle System.
43. Total value adjustment of Bermudan option valuation under pure jump Lévy fluctuations.
44. Neural network stochastic differential equation models with applications to financial data forecasting
45. Symplectic Euler scheme for Hamiltonian stochastic differential equations driven by Levy noise.
46. Symplectic method for Hamiltonian stochastic differential equations with multiplicative Lévy noise in the sense of Marcus.
47. Extracting Non-Gaussian Governing Laws from Data on Mean Exit Time.
48. Identifying stochastic governing equations from data of the most probable transition trajectories.
49. Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker-Planck Equation and Physics-informed Neural Networks.
50. A Data-Driven Approach for Discovering Stochastic Dynamical Systems with Non-Gaussian Levy Noise.
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