182 citations · 1.2k across the 59 of their papers we have counts for
16 papers · 1 filter
Universal Sentence Representation Learning with Conditional Masked Language Model
Ziyi Yang, Yinfei Yang, Daniel Cer +2
This paper presents a novel training method, Conditional Masked Language Modeling (CMLM), to effectively learn sentence representations on large scale unlabeled corpora. CMLM integ…
Integrating Deep Neural Networks with Full-waveform Inversion: Reparametrization, Regularization, and Uncertainty Quantification
Weiqiang Zhu, Kailai Xu, Eric Darve +2
Full-waveform inversion (FWI) is an accurate imaging approach for modeling velocity structure by minimizing the misfit between recorded and predicted seismic waveforms. However, th…
ADCME: Learning Spatially-varying Physical Fields using Deep Neural Networks
Kailai Xu, Eric Darve
ADCME is a novel computational framework to solve inverse problems involving physical simulations and deep neural networks (DNNs). This paper benchmarks its capability to learn spa…
Distributed Machine Learning for Computational Engineering using MPI
Kailai Xu, Weiqiang Zhu, Eric Darve
We propose a framework for training neural networks that are coupled with partial differential equations (PDEs) in a parallel computing environment. Unlike most distributed computi…
Hierarchical Orthogonal Factorization: Sparse Square matrices
Abeynaya Gnanasekaran, Eric Darve
In this work, we develop a new fast algorithm, spaQR -- sparsified QR, for solving large, sparse linear systems. The key to our approach is using low-rank approximations to sparsif…
Multi-Constitutive Neural Network for Large Deformation Poromechanics Problem
Qi Zhang, Yilin Chen, Ziyi Yang +1
In this paper, we study the problem of large-strain consolidation in poromechanics with deep neural networks (DNN). Given different material properties and different loading condit…