[Colloquium] Reminder: Hy/MS Presentation/Nov 1, 2018

[Margaret Jaffey via Colloquium]

This is a reminder about Truong Son Hy's MS Presentation on Thursday.

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Date:  Thursday, November 1, 2018

Time:  2:00 PM

Place:  John Crerar Library 298

M.S. Candidate:  Truong Son Hy

M.S. Paper Title: Covariant Compositional Networks for Learning Graphs
and GraphFlow Deep Learning framework in C++/CUDA

Abstract:
In this paper, we propose Covariant Compositional Networks (CCNs), the
state-of-the-art generalized convolution graph neural network for
learning graphs. By applying higher-order representations and tensor
contraction operations that are permutation-invariant with respect to
the set of vertices, CCNs address the representation limitation of all
existing neural networks for learning graphs in which permutation
invariance is only obtained by summation of feature vectors coming
from the neighbors for each vertex via well-known message passing
scheme. To efficiently implement graph neural networks and
high-complexity tensor operations in practice, we designed our custom
Deep Learning framework in C++ named GraphFlow that supports dynamic
computation graphs, automatic and symbolic differentiation as well as
tensor/matrix implementation in CUDA to speed-up computation with GPU.
For an application of graph neural networks in quantum chemistry and
molecular dynamics, we investigate the efficiency of CCNs in
estimating Density Functional Theory (DFT) that is the most successful
and widely used approach to compute the electronic structure of matter
but significantly expensive in computation. We obtain a very promising
result and outperform other state-of-the-art graph learning models in
Harvard Clean Energy Project and QM9 molecular datasets.

Index terms: graph neural network, message passing, density functional
theory, deep learning framework

Truong Son's advisor is Prof. Risi Kondor

Login to the Computer Science Department website for details:
 https://newtraell.cs.uchicago.edu/phd/ms_announcements#hytruongson

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Margaret P. Jaffey            margaret at cs.uchicago.edu
Department of Computer Science
Student Support Rep (Ry 156)               (773) 702-6011
The University of Chicago      http://www.cs.uchicago.edu
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