70 citations · 97 across the 17 of their papers we have counts for
20 papers
Score-Based Stabilization for Time-Dependent Problems
Eshed Gal, Eldad Haber, Uri Ascher
We propose a score-based stabilization framework for numerical simulation of partial differential equations, in which a learned score model defines a stabilization operator applied…
A Splitting Architecture for Exact Reduced Coulomb Friction
Hongcheng Song, Ye Fan, Uri M. Ascher +1
Existing approaches to frictional contact dynamics typically either modify the Coulomb law to improve numerical robustness or solve the exact law in a fully coupled monolithic form…
Target-Aware Data Augmentation for SAT Prediction
Eshed Gal, Uri Ascher, Eldad Haber
Learning-based approaches to NP-hard problems have shown increasing promise, but their progress is fundamentally constrained by the high cost of generating labeled training data. I…
Reversing Large Language Models for Efficient Training and Fine-Tuning
Eshed Gal, Moshe Eliasof, Javier Turek +3
Large Language Models (LLMs) are known for their expensive and time-consuming training. Thus, oftentimes, LLMs are fine-tuned to address a specific task, given the pretrained weigh…
Pitfalls of Projection: A study of Newton-type solvers for incremental potentials
Andreas Longva, Fabian Löschner, José Antonio Fernández-Fernández +3
Nonlinear systems arising from time integrators like Backward Euler can sometimes be reformulated as optimization problems, known as incremental potentials. We show through a compr…
Neural DAEs: Constrained neural networks
Tue Boesen, Eldad Haber, Uri Michael Ascher
This article investigates the effect of explicitly adding auxiliary algebraic trajectory information to neural networks for dynamical systems. We draw inspiration from the field of…
Implicit frictional dynamics with soft constraints
Egor Larionov, Andreas Longva, Uri M. Ascher +2
Dynamics simulation with frictional contacts is important for a wide range of applications, from cloth simulation to object manipulation. Recent methods using smoothed lagged frict…
Simulating deformable objects for computer animation: a numerical perspective
Uri M. Ascher, Egor Larionov, Seung Heon Sheen +1
We examine a variety of numerical methods that arise when considering dynamical systems in the context of physics-based simulations of deformable objects. Such problems arise in va…
Discrete Processes and their Continuous Limits
Uri M. Ascher
The possibility that a discrete process can be fruitfully approximated by a continuous one, with the latter involving a differential system, is fascinating. Important theoretical i…
Learning Elastic Constitutive Material and Damping Models
Bin Wang, Yuanmin Deng, Paul Kry +3
Commonly used linear and nonlinear constitutive material models in deformation simulation contain many simplifications and only cover a tiny part of possible material behavior. In…
Neural Material: Learning Elastic Constitutive Material and Damping Models from Sparse Data
Bin Wang, Paul Kry, Yuanmin Deng +3
The accuracy and fidelity of deformation simulations are highly dependent upon the underlying constitutive material model. Commonly used linear or nonlinear constitutive material m…
The Discrete Adjoint Method for Exponential Integration
Kai Rothauge, Eldad Haber, Uri Ascher
The implementation of the discrete adjoint method for exponential time differencing (ETD) schemes is considered. This is important for parameter estimation problems that are constr…
Local Volatility Models in Commodity Markets and Online Calibration
Vinicius Albani, Uri M. Ascher, Jorge P. Zubelli
We introduce a local volatility model for the valuation of options on commodity futures by using European vanilla option prices. The corresponding calibration problem is addressed…
Data driven recovery of local volatility surfaces
Vinicius Albani, Uri M. Ascher, Xu Yang +1
This paper examines issues of data completion and location uncertainty, popular in many practical PDE-based inverse problems, in the context of option calibration via recovery of l…
Numerical Computation of the Gradient and the Action of the Hessian for Time-Dependent PDE-Constrained Optimization Problems
Kai Rothauge, Eldad Haber, Uri Ascher
We present a systematic derivation of the algorithms required for computing the gradient and the action of the Hessian of an arbitrary misfit function for large-scale parameter est…
Algorithms that satisfy a stopping criterion, probably
Uri Ascher, Farbod Roosta-Khorasani
Iterative numerical algorithms are typically equipped with a stopping criterion, where the iteration process is terminated when some error or misfit measure is deemed to be below a…
Assessing stochastic algorithms for large scale nonlinear least squares problems using extremal probabilities of linear combinations of gamma random variables
Farbod Roosta-Khorasani, Gábor J. Székely, Uri Ascher
This article considers stochastic algorithms for efficiently solving a class of large scale non-linear least squares (NLS) problems which frequently arise in applications. We propo…
Data completion and stochastic algorithms for PDE inversion problems with many measurements
Farbod Roosta-Khorasani, Kees van den Doel, Uri Ascher
Inverse problems involving systems of partial differential equations (PDEs) with many measurements or experiments can be very expensive to solve numerically. In a recent paper we e…
Faster gradient descent and the efficient recovery of images
Hui Huang, Uri Ascher
Much recent attention has been devoted to gradient descent algorithms where the steepest descent step size is replaced by a similar one from a previous iteration or gets updated on…
Improved bounds on sample size for implicit matrix trace estimators
Farbod Roosta-Khorasani, Uri Ascher
This article is concerned with Monte-Carlo methods for the estimation of the trace of an implicitly given matrix whose information is only available through matrix-vector produ…