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Unconstrained Scene Generation with Locally Conditioned Radiance Fields


Apr 01, 2021
Terrance DeVries, Miguel Angel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind


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The GIST and RIST of Iterative Self-Training for Semi-Supervised Segmentation


Mar 31, 2021
Eu Wern Teh, Terrance DeVries, Brendan Duke, Ruowei Jiang, Parham Aarabi, Graham W. Taylor


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LOHO: Latent Optimization of Hairstyles via Orthogonalization


Mar 10, 2021
Rohit Saha, Brendan Duke, Florian Shkurti, Graham W. Taylor, Parham Aarabi

* CVPR 2021 

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SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation


Jan 21, 2021
Brendan Duke, Abdalla Ahmed, Christian Wolf, Parham Aarabi, Graham W. Taylor


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Building LEGO Using Deep Generative Models of Graphs


Dec 21, 2020
Rylee Thompson, Elahe Ghalebi, Terrance DeVries, Graham W. Taylor

* NeurIPS 2020 ML4eng workshop paper 

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Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization


Nov 12, 2020
Michal Lisicki, Arash Afkanpour, Graham W. Taylor

* Presented at Workshop on Learning Meets Combinatorial Algorithms at NeurIPS 2020 

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Identifying and interpreting tuning dimensions in deep networks


Nov 05, 2020
Nolan S. Dey, J. Eric Taylor, Bryan P. Tripp, Alexander Wong, Graham W. Taylor

* 14 pages, 12 figures, Shared Visual Representations in Human & Machine Intelligence NeurIPS Workshop 2020 

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Instance Selection for GANs


Jul 30, 2020
Terrance DeVries, Michal Drozdzal, Graham W. Taylor


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Generative Graph Perturbations for Scene Graph Prediction


Jul 11, 2020
Boris Knyazev, Harm de Vries, Cătălina Cangea, Graham W. Taylor, Aaron Courville, Eugene Belilovsky

* https://oolworkshop.github.io/program/ool_21.html, ICML Workshop 2020 on "Object-Oriented Learning (OOL): Perception, Representation, and Reasoning" 

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Enabling Continual Learning with Differentiable Hebbian Plasticity


Jun 30, 2020
Vithursan Thangarasa, Thomas Miconi, Graham W. Taylor

* Published as a conference paper at IJCNN 2020 

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Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation


May 17, 2020
Boris Knyazev, Harm de Vries, Cătălina Cangea, Graham W. Taylor, Aaron Courville, Eugene Belilovsky

* 17 pages, the code is available at https://github.com/bknyaz/sgg 

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Sample-Efficient Model-based Actor-Critic for an Interactive Dialogue Task


Apr 28, 2020
Katya Kudashkina, Valliappa Chockalingam, Graham W. Taylor, Michael Bowling


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ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis


Apr 02, 2020
Eu Wern Teh, Terrance DeVries, Graham W. Taylor


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Learning with less data via Weakly Labeled Patch Classification in Digital Pathology


Jan 10, 2020
Eu Wern Teh, Graham W. Taylor

* To appear in IEEE International Symposium on Biomedical Imaging (ISBI) 2020 

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Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking


Oct 28, 2019
Alaaeldin El-Nouby, Shuangfei Zhai, Graham W. Taylor, Joshua M. Susskind

* Holistic Video Understanding Workshop ICCV2019 

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A Nonparametric Bayesian Model for Sparse Temporal Multigraphs


Oct 11, 2019
Elahe Ghalebi, Hamidreza Mahyar, Radu Grosu, Graham W. Taylor, Sinead A. Williamson


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Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions


Sep 23, 2019
Boris Knyazev, Carolyn Augusta, Graham W. Taylor

* 14 pages, 7 figures 

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Image Classification with Hierarchical Multigraph Networks


Jul 21, 2019
Boris Knyazev, Xiao Lin, Mohamed R. Amer, Graham W. Taylor

* 13 pages, BMVC 2019 

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On the Evaluation of Conditional GANs


Jul 11, 2019
Terrance DeVries, Adriana Romero, Luis Pineda, Graham W. Taylor, Michal Drozdzal


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Batch Normalization is a Cause of Adversarial Vulnerability


May 29, 2019
Angus Galloway, Anna Golubeva, Thomas Tanay, Medhat Moussa, Graham W. Taylor

* To appear in the ICML 2019 Workshop on Identifying and Understanding Deep Learning Phenomena 

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Understanding attention in graph neural networks


May 08, 2019
Boris Knyazev, Graham W. Taylor, Mohamed R. Amer

* 8 pages, 2 tables, 5 figures, ICLR 2019 Workshop on Representation Learning on Graphs and Manifolds 

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Similarity Learning Networks for Animal Individual Re-Identification - Beyond the Capabilities of a Human Observer


Feb 21, 2019
Stefan Schneider, Graham W. Taylor, Stefan Linquist, Stefan C. Kremer

* 19 pages, 7 figures, 1 table. To be submitted. arXiv admin note: substantial text overlap with arXiv:1811.07749 

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SISC: End-to-end Interpretable Discovery Radiomics-Driven Lung Cancer Prediction via Stacked Interpretable Sequencing Cells


Jan 15, 2019
Vignesh Sankar, Devinder Kumar, David A. Clausi, Graham W. Taylor, Alexander Wong

* First two authors have equal contribution 

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Adversarial Examples as an Input-Fault Tolerance Problem


Nov 30, 2018
Angus Galloway, Anna Golubeva, Graham W. Taylor

* NIPS 2018 Workshop on Security and Machine Learning. Source available at https://github.com/uoguelph-mlrg/nips18-secml-advex-input-fault 

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Keep Drawing It: Iterative language-based image generation and editing


Nov 24, 2018
Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz, Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio, Graham W. Taylor


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Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules


Nov 23, 2018
Boris Knyazev, Xiao Lin, Mohamed R. Amer, Graham W. Taylor

* 11 pages, 5 figures, NIPS 2018 Workshop on Machine Learning for Molecules and Materials 

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Past, Present, and Future Approaches Using Computer Vision for Animal Re-Identification from Camera Trap Data


Nov 19, 2018
Stefan Schneider, Graham W. Taylor, Stefan S. Linquist, Stefan C. Kremer

* 25 pages, 1 picture 

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Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points


Aug 21, 2018
Fabien Baradel, Christian Wolf, Julien Mille, Graham W. Taylor

* CVPR 2018 
* CVPR 2018 - project page: https://fabienbaradel.github.io/cvpr18_glimpseclouds/ 

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