28 citations · 71 across the 19 of their papers we have counts for
20 papers
A Stabilized Path-Space Approach to Diffusion-Based Posterior Sampling
Evan Scope Crafts, Umberto Villa, Saviz Mowlavi +3
Diffusion models provide expressive data-driven priors for Bayesian inverse problems, but many diffusion posterior samplers rely on heuristic guidance approximations that can fail…
OpInf-LLM: Parametric PDE Solving with LLMs via Operator Inference
Zhuoyuan Wang, Hanjiang Hu, Xiyu Deng +2
Solving diverse partial differential equations (PDEs) is fundamental in science and engineering. Large language models (LLMs) have demonstrated strong capabilities in code generati…
AB-PINNs: Adaptive-Basis Physics-Informed Neural Networks for Residual-Driven Domain Decomposition
Jonah Botvinick-Greenhouse, Wael H. Ali, Mouhacine Benosman +1
We introduce adaptive-basis physics-informed neural networks (AB-PINNs), a novel approach to domain decomposition for training PINNs in which existing subdomains dynamically adapt…
A Dual Ensemble Kalman Filter Approach to Robust Control of Nonlinear Systems: An Application to Partial Differential Equations
Anant A. Joshi, Saviz Mowlavi, Mouhacine Benosman
This paper considers the problem of data-driven robust control design for nonlinear systems, for instance, obtained when discretizing nonlinear partial differential equations (PDEs…
Policy Optimization for PDE Control with a Warm Start
Xiangyuan Zhang, Saviz Mowlavi, Mouhacine Benosman +1
Dimensionality reduction is crucial for controlling nonlinear partial differential equations (PDE) through a "reduce-then-design" strategy, which identifies a reduced-order model a…
Smooth and Sparse Latent Dynamics in Operator Learning with Jerk Regularization
Xiaoyu Xie, Saviz Mowlavi, Mouhacine Benosman
Spatiotemporal modeling is critical for understanding complex systems across various scientific and engineering disciplines, but governing equations are often not fully known or co…
OptiState: State Estimation of Legged Robots using Gated Networks with Transformer-based Vision and Kalman Filtering
Alexander Schperberg, Yusuke Tanaka, Saviz Mowlavi +3
State estimation for legged robots is challenging due to their highly dynamic motion and limitations imposed by sensor accuracy. By integrating Kalman filtering, optimization, and…
Dual parametric and state estimation for partial differential equations
Saviz Mowlavi, Mouhacine Benosman
Designing estimation algorithms for systems governed by partial differential equations (PDEs) such as fluid flows is challenging due to the high-dimensional and oftentimes nonlinea…
Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms
Xiangyuan Zhang, Weichao Mao, Saviz Mowlavi +2
We introduce controlgym, a library of thirty-six industrial control settings, and ten infinite-dimensional partial differential equation (PDE)-based control problems. Integrated wi…
Global Convergence of Receding-Horizon Policy Search in Learning Estimator Designs
Xiangyuan Zhang, Saviz Mowlavi, Mouhacine Benosman +1
We introduce the receding-horizon policy gradient (RHPG) algorithm, the first PG algorithm with provable global convergence in learning the optimal linear estimator designs, i.e.,…
Detecting hidden structures from a static loading experiment: topology optimization meets physics-informed neural networks
Saviz Mowlavi, Ken Kamrin
Most noninvasive imaging techniques utilize electromagnetic or acoustic waves originating from multiple locations and directions to identify hidden geometrical structures. Surprisi…
Reinforcement learning-based estimation for partial differential equations
Saviz Mowlavi, Mouhacine Benosman
In systems governed by nonlinear partial differential equations such as fluid flows, the design of state estimators such as Kalman filters relies on a reduced-order model (ROM) tha…
Optimal control of PDEs using physics-informed neural networks
Saviz Mowlavi, Saleh Nabi
Physics-informed neural networks (PINNs) have recently become a popular method for solving forward and inverse problems governed by partial differential equations (PDEs). By incorp…
Detecting Lagrangian coherent structures from sparse and noisy trajectory data
Saviz Mowlavi, Mattia Serra, Enrico Maiorino +1
Many complex flows such as those arising from ocean plastics in geophysics or moving cells in biology are characterized by sparse and noisy trajectory datasets. We introduce techni…
Interplay between hysteresis and nonlocality during onset and arrest of flow in granular materials
Saviz Mowlavi, Ken Kamrin
The jamming transition in granular materials is well-known for exhibiting hysteresis, wherein the level of shear stress required to trigger flow is larger than that below which flo…
Reduced model for capillary breakup with thermal gradients: Predictions and computational validation
Isha Shukla, Fan Wang, Saviz Mowlavi +4
It was recently demonstrated that feeding a silicon-in-silica coaxial fibre into a flameimparting a steep silica viscosity gradientresults in the formatio…
Contact model for elastically anisotropic bodies and efficient implementation into the discrete-element method
Saviz Mowlavi, Ken Kamrin
We introduce a contact law for the normal force generated between two contacting, elastically anisotropic bodies of arbitrary geometry. The only requirement is that their surfaces…
Particle size selection in capillary instability of locally heated co-axial fiber
Saviz Mowlavi, Isha Shukla, PT Brun +1
Harnessing fluidic instabilities to produce structures with robust and regular properties has recently emerged as a new fabrication paradigm. This is exemplified in the work of Gum…
Absolute/convective secondary instabilities and the role of confinement in free shear layers
Cristobal Arratia, Saviz Mowlavi, Francois Gallaire
Mixing layers can grow in time or space by vortex pairings that succeed each other in a nearly self-similar way. We use a point vortex model to study how confinement eventually lim…
Model order reduction for stochastic dynamical systems with continuous symmetries
Saviz Mowlavi, Themistoklis P. Sapsis
Stochastic dynamical systems with continuous symmetries arise commonly in nature and often give rise to coherent spatio-temporal patterns. However, because of their random location…