
A Hybrid DirectIterative Method for Solving KKT Linear Systems
We propose a solution strategy for linear systems arising in interior me...
read it

A Simple and Effective Method To Eliminate the Self Language Bias in Multilingual Representations
Language agnostic and semanticlanguage information isolation is an emer...
read it

Linear solvers for power grid optimization problems: a review of GPUaccelerated linear solvers
The linear equations that arise in interior methods for constrained opti...
read it

Trust Region Method for Coupled Systems of PDE Solvers and Deep Neural Networks
Physicsinformed machine learning and inverse modeling require the solut...
read it

Hierarchical Orthogonal Factorization: Sparse Least Squares Problems
In this work, we develop a fast hierarchical solver for solving large, s...
read it

Towards a Scalable Hierarchical Highorder CFD Solver
Development of highly scalable and robust algorithms for largescale CFD...
read it

Universal Sentence Representation Learning with Conditional Masked Language Model
This paper presents a novel training method, Conditional Masked Language...
read it

ADCME: Learning Spatiallyvarying Physical Fields using Deep Neural Networks
ADCME is a novel computational framework to solve inverse problems invol...
read it

Application of Deep Learningbased Interpolation Methods to Nearshore Bathymetry
Nearshore bathymetry, the topography of the ocean floor in coastal zones...
read it

Distributed Machine Learning for Computational Engineering using MPI
We propose a framework for training neural networks that are coupled wit...
read it

Hierarchical Orthogonal Factorization: Sparse Square matrices
In this work, we develop a new fast algorithm, spaQR – sparsified QR, fo...
read it

TaskTorrent: a Lightweight Distributed TaskBased Runtime System in C++
We present TaskTorrent, a lightweight distributed taskbased runtime in ...
read it

Solving Inverse Problems in Steady State NavierStokes Equations using Deep Neural Networks
Inverse problems in fluid dynamics are ubiquitous in science and enginee...
read it

Second Order Accurate Hierarchical Approximate Factorization of Sparse SPD Matrices
We describe a secondorder accurate approach to sparsifying the offdiag...
read it

Anomaly Detection with Domain Adaptation
We study the problem of semisupervised anomaly detection with domain ad...
read it

Inverse Modeling of Viscoelasticity Materials using Physics Constrained Learning
We propose a novel approach to model viscoelasticity materials using neu...
read it

Learning Constitutive Relations using Symmetric Positive Definite Neural Networks
We present the Choleskyfactored symmetric positive definite neural netw...
read it

Physics Constrained Learning for Datadriven Inverse Modeling from Sparse Observations
Deep neural networks (DNN) have been used to model nonlinear relations b...
read it

Memory Augmented Generative Adversarial Networks for Anomaly Detection
In this paper, we present a memoryaugmented algorithm for anomaly detec...
read it

Regularized Cycle Consistent Generative Adversarial Network for Anomaly Detection
In this paper, we investigate algorithms for anomaly detection. Previous...
read it

Learning Hidden Dynamics using Intelligent Automatic Differentiation
Many engineering problems involve learning hidden dynamics from indirect...
read it

Adversarial Numerical Analysis for Inverse Problems
Many scientific and engineering applications are formulated as inverse p...
read it

Sparse Hierarchical Preconditioners Using Piecewise Smooth Approximations of Eigenvectors
When solving linear systems arising from PDE discretizations, iterative ...
read it

Embedding Imputation with Grounded Language Information
Due to the ubiquitous use of embeddings as input representations for a w...
read it

PBBFMM3D: a parallel blackbox algorithm for kernel matrixvector multiplication
We introduce PBBFMM3D, a parallel blackbox method for computing kernel ...
read it

PBBFMM3D: a Parallel BlackBox Fast Multipole Method for Nonoscillatory Kernels
This paper presents PBBFMM3D: a parallel blackbox fast multipole method...
read it

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...
read it

A distributedmemory hierarchical solver for general sparse linear systems
We present a parallel hierarchical solver for general sparse linear syst...
read it

On the numerical rank of radial basis function kernels in high dimension
Lowrank approximations are popular methods to reduce the high computati...
read it

On the numerical rank of radial basis function kernel matrices in high dimension
Lowrank approximations are popular techniques to reduce the high comput...
read it

Structured Block Basis Factorization for Scalable Kernel Matrix Evaluation
Kernel matrices are popular in machine learning and scientific computing...
read it
Eric Darve
is this you? claim profile