recent.bib

@comment{{This file has been generated by bib2bib 1.99}}
@comment{{Command line: bib2bib -ob src/recent.bib -c '$key="knyazev2020predicting" or $key="dey2020identifying" or $key="lisicki2020evaluating" or $key="thompson2020building" or $key="devries2020instance" or $key="knyazev2020graph" or $key="knyazev2020generative" or $key="taylor2020response" or $key="teh2020proxy" or $key="kalra2019learning" or $key="elnouby2019skip" or $key="devries2019evaluation" or $key="knyazev2019generalization" or $key="elnouby2019tell" or $key="knyazev2019image" or $key="galloway2019abatch" or $key="murali2019classification" or $key="galloway2018fault" or $key="knyazev2018spectral" or $key="lacey2018stochastic" or $key="devries2018leveraging" or $key="schneider2018acan" or $key="galloway2018aadversarial" or $key="baradel2018glimpse" or $key="galloway2018predicting" or $key="devries2018learning" or $key="galloway2018attacking" or $key="im2018quantitatively"' research-common/gwt_pubs.bib}}
@inproceedings{thompson2020building,
  author = {Rylee Thompson and Elahe Ghalebi and Terrance DeVries and Graham Taylor},
  title = {Building {LEGO} Using Deep Generative Models of Graphs},
  booktitle = {Neural Information Processing Systems (NeurIPS) Workshop on Machine Learning for Engineering Modeling, Simulation, and Design},
  pdf = {https://arxiv.org/abs/2012.11543},
  year = 2020
}
@inproceedings{lisicki2020evaluating,
  author = {Michal Lisicki and Arash Afkanpour and Graham Taylor},
  title = {Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization},
  booktitle = {Neural Information Processing Systems (NeurIPS) Workshop on Learning Meets Combinatorial Algorithms},
  pdf = {https://arxiv.org/abs/2011.06188},
  year = 2020
}
@inproceedings{dey2020identifying,
  author = {Nolan Dey and Eric Taylor and Bryan Tripp and Alexander Wong and Graham Taylor},
  title = {Identifying and interpreting tuning dimensions in deep networks},
  booktitle = {Neural Information Processing Systems (NeurIPS) Workshop on Shared Visual Representations in Human and Machine Intelligence},
  pdf = {https://arxiv.org/abs/2011.03043},
  year = 2020
}
@inproceedings{knyazev2020predicting,
  author = {Boris Knyazev and Michal Drozdzal and Graham Taylor and Adriana Romero},
  title = {Predicting Pretrained Weights of Large-scale {CNN}s},
  booktitle = {Neural Information Processing Systems (NeurIPS) Workshop on Beyond Backpropagation: Novel Ideas for Training Neural Architectures},
  year = 2020
}
@inproceedings{devries2020instance,
  author = {Terrance DeVries and Michal Drozdzal and Graham Taylor},
  title = {Instance Selection for {GANs}},
  booktitle = {Neural Information Processing Systems (NeurIPS)},
  pdf = {https://arxiv.org/abs/2007.15255},
  year = 2020
}
@inproceedings{knyazev2020graph,
  author = {Boris Knyazev and Harm de Vries and Cătălina Cangea and Graham Taylor and Aaron Courville and Eugene Belilovsky},
  title = {Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation},
  booktitle = {British Machine Vision Conference (BMVC)},
  year = 2020,
  pdf = {https://arxiv.org/abs/2005.08230}
}
@inproceedings{taylor2020response,
  author = {Eric Taylor and Shashank Shekhar and Graham Taylor},
  title = {Response Time Analysis for Explainability of Visual Processing in {CNNs}},
  booktitle = {{IEEE} CVPR Workshop on Minds vs.~Machines: How Far Are We From the Common Sense of a Toddler?},
  year = 2020,
  pdf = {https://openaccess.thecvf.com/content_CVPRW_2020/html/w26/Taylor_Response_Time_Analysis_for_Explainability_of_Visual_Processing_in_CNNs_CVPRW_2020_paper.html}
}
@inproceedings{teh2020proxy,
  author = {{Eu Wern} Teh and Terrance DeVries and Graham Taylor},
  title = {{ProxyNCA++}: Revisiting and Revitalizing Proxy Neighborhood Component Analysis},
  booktitle = {European Conference on Computer Vision (ECCV)},
  pdf = {https://arxiv.org/abs/2004.01113},
  year = 2020
}
@inproceedings{kalra2019learning,
  author = {Shivam Kalra and Mohammad Adnan and Graham Taylor and Hamid Tizhoosh},
  title = {Learning Permutation Invariant Representations using Memory Networks},
  booktitle = {European Conference on Computer Vision (ECCV)},
  pdf = {https://arxiv.org/abs/1911.07984},
  year = 2020
}
@inproceedings{elnouby2019skip,
  author = {Alaaeldin El-Nouby and Shuangfei Zhai and Graham Taylor and Joshua Susskind},
  title = {Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking},
  booktitle = {International Conference on Computer Vision (ICCV) Workshop on Holistic Video Understanding},
  year = 2019,
  pdf = {https://arxiv.org/abs/1910.12770}
}
@article{devries2019evaluation,
  author = {Terrance DeVries and Adriana Romero and Luis Pineda and Graham Taylor and Michal Drozdzal},
  title = {On the Evaluation of Conditional {GANs}},
  journal = {arXiv preprint arXiv:1907.08175},
  pdf = {https://arxiv.org/abs/1907.08175},
  year = 2019
}
@inproceedings{knyazev2019generalization,
  author = {Boris Knyazev and Graham Taylor and Mohamed Amer},
  title = {Understanding Attention and Generalization in Graph Neural Networks},
  booktitle = {Neural Information Processing Systems (NeurIPS)},
  year = 2019,
  pdf = {http://arxiv.org/abs/1905.02850},
  note = {Early version appeared at the International Conference on Learning Representations (ICLR) Workshop on Representation Learning on Graphs and Manifolds.}
}
@inproceedings{elnouby2019tell,
  author = {Alaaeldin El-Nouby and Shikhar Sharma and Hannes Schulz and Devon Hjelm and El Asri, Layla and Ebrahimi Kahou, Samira and Yoshua Bengio and Graham Taylor},
  title = {Tell, Draw, and Repeat: Generating and modifying images based on continual linguistic instruction},
  booktitle = {International Conference on Computer Vision (ICCV)},
  note = {Early version appeared at the Neural Information Processing Systems (NeurIPS) Workshop on Visually Grounded Interaction and Language (ViGIL)},
  pdf = {https://arxiv.org/abs/1811.09845}
}
@inproceedings{knyazev2019image,
  author = {Boris Knyazev and Xiao Lin and Mohamed Amer and Graham Taylor},
  title = {Image Classification with Hierarchical Multigraph Networks},
  booktitle = {British Machine Vision Conference (BMVC)},
  year = 2019,
  pdf = {http://arxiv.org/abs/1907.09000}
}
@inproceedings{galloway2019abatch,
  author = {Angus Galloway and Anna Golubeva and Thomas Tanay and Medhat Moussa and Graham Taylor},
  title = {Batch Normalization is a Cause of Adversarial Vulnerability},
  booktitle = {International Conference on Machine Learning (ICML) Workshop on Identifying and Understanding Deep Learning Phenomena},
  year = 2019,
  pdf = {https://arxiv.org/abs/1905.02161}
}
@inproceedings{galloway2018fault,
  author = {Angus Galloway and Anna Golubeva and Graham Taylor},
  title = {Adversarial Examples as an Input-Fault Tolerance Problem},
  booktitle = {Neural Information Processing Systems (NeurIPS) Workshop on Security in Machine Learning},
  year = 2018,
  pdf = {https://arxiv.org/abs/1811.12601}
}
@inproceedings{knyazev2018spectral,
  author = {Boris Knyazev and Lin, Xiao and Amer, Mohamed R. and Graham Taylor},
  title = {Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules},
  booktitle = {Neural Information Processing Systems (NeurIPS) Workshop on Machine Learning for Molecules and Materials},
  year = 2018,
  pdf = {https://arxiv.org/abs/1811.09595}
}
@inproceedings{murali2019classification,
  author = {Nihal Murali and Jonathan Schneider and Joel Levine and Graham Taylor},
  title = {Classification and Re-Identification of Fruit Fly Individuals Across Days with Convolutional Neural Networks},
  booktitle = {{IEEE} Winter Conference on Applications of Computer Vision (WACV)},
  year = 2019,
  pages = {570--578},
  pdf = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8658974}
}
@article{schneider2018acan,
  author = {Jonathan Schneider and Nihal Murali and Graham Taylor and Joel Levine},
  title = {Can {Drosophila melanogaster} tell who's who?},
  journal = {PLOS One},
  volume = 13,
  number = 10,
  year = 2018
}
@inproceedings{lacey2018stochastic,
  author = {Griffin Lacey and Graham Taylor and Shawki Areibi},
  title = {Stochastic Layer-Wise Precision in Deep Neural Networks},
  booktitle = {Uncertainty in Artificial Intelligence ({UAI})},
  year = 2018,
  pdf = {https://arxiv.org/abs/1807.00942}
}
@article{devries2018leveraging,
  author = {Terrance DeVries and Graham Taylor},
  title = {Leveraging Uncertainty Estimates for Predicting Segmentation Quality},
  journal = {arXiv preprint arXiv:1807.00502},
  pdf = {https://arxiv.org/abs/1807.00502},
  year = 2018
}
@article{galloway2018aadversarial,
  author = {Angus Galloway and Thomas Tanay and Graham Taylor},
  title = {Adversarial Training Versus Weight Decay},
  journal = {arXiv preprint arXiv:1802.04457},
  pdf = {https://arxiv.org/abs/1804.03308},
  year = 2018
}
@inproceedings{baradel2018glimpse,
  author = {Fabien Baradel and Christian Wolf and Julien Mille and Graham Taylor},
  title = {Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points},
  booktitle = {Proc.~of the 31st {IEEE} Computer Society Conference on Computer Vision and Pattern Recognition ({CVPR})},
  pdf = {https://arxiv.org/abs/1802.07898},
  year = 2018
}
@article{galloway2018predicting,
  author = {Angus Galloway and Graham Taylor and Medhat Moussa},
  title = {Predicting Adversarial Examples with High Confidence},
  journal = {arXiv preprint arXiv:1802.04457},
  pdf = {https://arxiv.org/abs/1802.04457},
  year = 2018
}
@article{devries2018learning,
  author = {Terrance DeVries and Graham Taylor},
  title = {Learning Confidence for Out-of-Distribution Detection in Neural Networks},
  journal = {arXiv preprint arXiv:1802.04865},
  pdf = {https://arxiv.org/abs/1802.04865},
  year = 2018
}
@inproceedings{im2018quantitatively,
  author = {Daniel Jiwoong Im and He Ma and Graham Taylor and Kristen Branson},
  title = {Quantitatively Evaluating {GANs} with Divergences Proposed for Training},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = 2018,
  pdf = {https://arxiv.org/abs/1803.01045}
}
@inproceedings{galloway2018attacking,
  author = {Angus Galloway and Graham Taylor and Medhat Moussa},
  title = {Attacking Binarized Neural Networks},
  booktitle = {International Conference on Learning Representations ({ICLR})},
  pdf = {https://arxiv.org/abs/1711.00449},
  year = 2018
}