Jeroen's Home Page

Jeroen

CV

CV
Last updated: August 2017

About

Hi! I've completed my PhD and have joined Google. Prior to joining Google, I did my PhD at Brown on a large-scale probabilistic models, and developing a unified framework for scene understanding (see my thesis). Prior to that, I completed my Master's at the University of Toronto under Brendan Frey; my Master's topic was separating shape from colour for mid-level image representations.

I'm in interested machine learning (hybrid deep learning/probabilistic frameworks, Bayesian modeling/inference, hierarchical models, probabilistic grammars) and computer vision (object detection/localization/tracking, scene understanding, virtual and augmented reality).

Contact Info

Email: jeroen_chua at X.edu
X = brown

Office: Thomas J. Watson Sr. Center for Information Technology (CIT)- Room 423
115 Waterman Street, Providence, RI 02912

Recent work

Factor Flow (version: alpha): A flexible, powerful framework for message-based approximate inference schemes in factor graphs. Supports sum-product loopy belief propagation, max-product BP, Tree Re-weighted BP, Convergent BP.

Thesis: Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding.
Defense Slides


Other publications: I'm doing the un-stapled PhD and will be chopping up my PhD thesis into several publications. I'll put an arxiv link to them after submission. The core of the work will be submitted Nto eural Computation(in preparation; to be submitted in November).

Conference Papers

Learning Structural Element Patch Models with Hierarchical Palettes
Jeroen C. Chua, Inmar E. Givoni, Ryan P. Adams, Brendan J. Frey
"IEEE Conference on Computer Vision and Pattern Recognition 2012".
pdf

Workshop Abstracts and Papers

Sparse coding with stel dictionaries
Jeroen Chua, Brendan Frey
"Snowbird Learning Workshop, 2012" (Oral presentation)
slides

Bayesian Painting by Numbers: Flexible Priors for Colour-Invariant Object Recognition
J.C. Chua, I.E. Givoni, R.P. Adams, B.J. Frey
"Computer Vision and Machine Learning for Image and Video Analysis", Eds. R. Cipolla, S. Battiato and G. M. Farinella (2012), Studies in Computational Intelligence, Springer-Verlag Berlin Heidelberg.
pdf

Unrefereed publications

PhD Thesis
J.C. Chua
"Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding"
Thesis*NEW*
Defense Slides *NEW*

Scene Grammars, Factor Graphs, and Belief Propagation
J. Chua, P. Felzenszwalb
pdf

Master's Thesis
J.C. Chua
"Learning Patch-Based Structural Element Models With Hierarchical Palettes"
pdf

Teaching

Winter 2016 - Topics in Optimizaiton
Fall 2014 - CS242 Probabilistic Graphical Models
Winter 2010 - ECE244 Programming Fundamentals