18 citations · 19 across the 2 of their papers we have counts for
7 papers
Directed Graph Auto-Encoders
Georgios Kollias, Vasileios Kalantzis, Tsuyoshi Idé +2
We introduce a new class of auto-encoders for directed graphs, motivated by a direct extension of the Weisfeiler-Leman algorithm to pairs of node labels. The proposed model learns…
Projection techniques to update the truncated SVD of evolving matrices
Vassilis Kalantzis, Georgios Kollias, Shashanka Ubaru +3
This paper considers the problem of updating the rank-k truncated Singular Value Decomposition (SVD) of matrices subject to the addition of new rows and/or columns over time. Such…
Accelerating Physics-Based Simulations Using Neural Network Proxies: An Application in Oil Reservoir Modeling
Jiri Navratil, Alan King, Jesus Rios +3
We develop a proxy model based on deep learning methods to accelerate the simulations of oil reservoirs--by three orders of magnitude--compared to industry-strength physics-based P…
Low rank methods for multiple network alignment
Huda Nassar, Georgios Kollias, Ananth Grama +1
Multiple network alignment is the problem of identifying similar and related regions in a given set of networks. While there are a large number of effective techniques for pairwise…
Provably convergent acceleration in factored gradient descent with applications in matrix sensing
Tayo Ajayi, David Mildebrath, Anastasios Kyrillidis +3
We present theoretical results on the convergence of \emph{non-convex} accelerated gradient descent in matrix factorization models with -norm loss. The purpose of this work…
MXNET-MPI: Embedding MPI parallelism in Parameter Server Task Model for scaling Deep Learning
Amith R Mamidala, Georgios Kollias, Chris Ward +1
Existing Deep Learning frameworks exclusively use either Parameter Server(PS) approach or MPI parallelism. In this paper, we discuss the drawbacks of such approaches and propose a…