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09/05/2023
Resilient VAE: Unsupervised Anomaly Detection at the SLAC Linac Coherent Light Source
Significant advances in utilizing deep learning for anomaly detection ha...
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03/15/2023
A numerically stable communication-avoiding s-step GMRES algorithm
Krylov subspace methods are extensively used in scientific computing to ...
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03/13/2023
Learning Reduced-Order Models for Cardiovascular Simulations with Graph Neural Networks
Reduced-order models based on physics are a popular choice in cardiovasc...
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02/16/2023
Physics-based parameterized neural ordinary differential equations: prediction of laser ignition in a rocket combustor
In this work, we present a novel physics-based data-driven framework for...
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10/06/2022
Probabilistic partition of unity networks for high-dimensional regression problems
We explore the probabilistic partition of unity network (PPOU-Net) model...
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10/07/2021
A Hybrid Direct-Iterative Method for Solving KKT Linear Systems
We propose a solution strategy for linear systems arising in interior me...
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09/10/2021
A Simple and Effective Method To Eliminate the Self Language Bias in Multilingual Representations
Language agnostic and semantic-language information isolation is an emer...
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06/25/2021
Linear solvers for power grid optimization problems: a review of GPU-accelerated linear solvers
The linear equations that arise in interior methods for constrained opti...
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05/17/2021
Trust Region Method for Coupled Systems of PDE Solvers and Deep Neural Networks
Physics-informed machine learning and inverse modeling require the solut...
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02/19/2021
Hierarchical Orthogonal Factorization: Sparse Least Squares Problems
In this work, we develop a fast hierarchical solver for solving large, s...
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01/05/2021
Towards a Scalable Hierarchical High-order CFD Solver
Development of highly scalable and robust algorithms for large-scale CFD...
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12/28/2020
Universal Sentence Representation Learning with Conditional Masked Language Model
This paper presents a novel training method, Conditional Masked Language...
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11/24/2020
ADCME: Learning Spatially-varying Physical Fields using Deep Neural Networks
ADCME is a novel computational framework to solve inverse problems invol...
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11/19/2020
Application of Deep Learning-based Interpolation Methods to Nearshore Bathymetry
Nearshore bathymetry, the topography of the ocean floor in coastal zones...
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11/02/2020
Distributed Machine Learning for Computational Engineering using MPI
We propose a framework for training neural networks that are coupled wit...
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10/14/2020
Hierarchical Orthogonal Factorization: Sparse Square matrices
In this work, we develop a new fast algorithm, spaQR – sparsified QR, fo...
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09/22/2020
TaskTorrent: a Lightweight Distributed Task-Based Runtime System in C++
We present TaskTorrent, a lightweight distributed task-based runtime in ...
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08/30/2020
Solving Inverse Problems in Steady State Navier-Stokes Equations using Deep Neural Networks
Inverse problems in fluid dynamics are ubiquitous in science and enginee...
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07/01/2020
Second Order Accurate Hierarchical Approximate Factorization of Sparse SPD Matrices
We describe a second-order accurate approach to sparsifying the off-diag...
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06/05/2020
Anomaly Detection with Domain Adaptation
We study the problem of semi-supervised anomaly detection with domain ad...
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05/09/2020
Inverse Modeling of Viscoelasticity Materials using Physics Constrained Learning
We propose a novel approach to model viscoelasticity materials using neu...
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04/01/2020
Learning Constitutive Relations using Symmetric Positive Definite Neural Networks
We present the Cholesky-factored symmetric positive definite neural netw...
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02/24/2020
Physics Constrained Learning for Data-driven Inverse Modeling from Sparse Observations
Deep neural networks (DNN) have been used to model nonlinear relations b...
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02/07/2020
Memory Augmented Generative Adversarial Networks for Anomaly Detection
In this paper, we present a memory-augmented algorithm for anomaly detec...
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01/18/2020
Regularized Cycle Consistent Generative Adversarial Network for Anomaly Detection
In this paper, we investigate algorithms for anomaly detection. Previous...
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12/16/2019
Learning Hidden Dynamics using Intelligent Automatic Differentiation
Many engineering problems involve learning hidden dynamics from indirect...
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10/15/2019
Adversarial Numerical Analysis for Inverse Problems
Many scientific and engineering applications are formulated as inverse p...
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07/08/2019
Sparse Hierarchical Preconditioners Using Piecewise Smooth Approximations of Eigenvectors
When solving linear systems arising from PDE discretizations, iterative ...
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06/10/2019
Embedding Imputation with Grounded Language Information
Due to the ubiquitous use of embeddings as input representations for a w...
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03/06/2019
PBBFMM3D: a parallel black-box algorithm for kernel matrix-vector multiplication
We introduce PBBFMM3D, a parallel black-box method for computing kernel ...
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03/06/2019
PBBFMM3D: a Parallel Black-Box Fast Multipole Method for Non-oscillatory Kernels
This paper presents PBBFMM3D: a parallel black-box fast multipole method...
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12/20/2018
Calibrating Lévy Process from Observations Based on Neural Networks and Automatic Differentiation with Convergence Proofs
The Lévy process has been widely applied to mathematical finance, quantu...
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12/20/2017
A distributed-memory hierarchical solver for general sparse linear systems
We present a parallel hierarchical solver for general sparse linear syst...
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06/23/2017
On the numerical rank of radial basis function kernels in high dimension
Low-rank approximations are popular methods to reduce the high computati...
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06/23/2017
On the numerical rank of radial basis function kernel matrices in high dimension
Low-rank approximations are popular techniques to reduce the high comput...
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05/03/2015
