6 papers
First-Order Trajectory Matching: Fast Ensemble Predictions of Chaotic, Turbulent, Stochastic Systems
Shreya Jha, Timo Schorlepp, Nicholas Geissler +2
We introduce First-Order Trajectory Matching (FTM), a surrogate-modeling method that learns the first-order local transport of probability mass from trajectories of stochastic syst…
Intermittency from instanton calculus at the transition to turbulence and fusion rules
Timo Schorlepp, Rainer Grauer
Understanding intermittency of turbulent systems from the underlying differential equations is an outstanding problem in fluid dynamics. Here, in the example of Burgers turbulence…
Scalability of the second-order reliability method for stochastic differential equations with multiplicative noise
Timo Schorlepp, Tobias Grafke
We show how to efficiently compute asymptotically sharp estimates of extreme event probabilities in stochastic differential equations (SDEs) with small multiplicative Brownian nois…
Precise asymptotic analysis of Sobolev training for random feature models
Katharine E Fisher, Matthew TC Li, Youssef Marzouk +1
Gradient information is widely useful and available in applications, and is therefore natural to include in the training of neural networks. Yet little is known theoretically about…
Synthetic Turbulence via an Instanton Gas Approximation
Timo Schorlepp, Katharina Kormann, Jeremiah Lübke +2
Sampling synthetic turbulent fields as a computationally tractable surrogate for direct numerical simulations (DNS) is an important practical problem in various applications, and a…
Systematic analysis of critical exponents in continuous dynamical phase transitions of weak noise theories
Timo Schorlepp, Ohad Shpielberg
Dynamical phase transitions are nonequilibrium counterparts of thermodynamic phase transitions and share many similarities with their equilibrium analogs. In continuous phase trans…