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Graham W. Taylor
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- affiliation: University of Guelph, Guelph, ON, Canada
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2020 – today
- 2024
- [j20]Mingjie Wang, Yande Li, Jun Zhou, Graham W. Taylor, Minglun Gong:
GCNet: Probing self-similarity learning for Generalized Counting Network. Pattern Recognit. 153: 110513 (2024) - [c84]Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor, Thomas B. Moeslund:
Agglomerative Token Clustering. ECCV (57) 2024: 200-218 - [i91]Akshita Gupta, Gaurav Mittal, Ahmed Magooda, Ye Yu, Graham W. Taylor, Mei Chen:
LoSA: Long-Short-range Adapter for Scaling End-to-End Temporal Action Localization. CoRR abs/2404.01282 (2024) - [i90]ZeMing Gong, Austin T. Wang, Joakim Bruslund Haurum, Scott C. Lowe, Graham W. Taylor, Angel X. Chang:
BIOSCAN-CLIP: Bridging Vision and Genomics for Biodiversity Monitoring at Scale. CoRR abs/2405.17537 (2024) - [i89]Kevin Kasa, Zhiyu Zhang, Heng Yang, Graham W. Taylor:
Adapting Conformal Prediction to Distribution Shifts Without Labels. CoRR abs/2406.01416 (2024) - [i88]Scott C. Lowe, Joakim Bruslund Haurum, Sageev Oore, Thomas B. Moeslund, Graham W. Taylor:
An Empirical Study into Clustering of Unseen Datasets with Self-Supervised Encoders. CoRR abs/2406.02465 (2024) - [i87]Zahra Gharaee, Scott C. Lowe, ZeMing Gong, Pablo Millan Arias, Nicholas Pellegrino, Austin T. Wang, Joakim Bruslund Haurum, Iuliia Zarubiieva, Lila Kari, Dirk Steinke, Graham W. Taylor, Paul W. Fieguth, Angel X. Chang:
BIOSCAN-5M: A Multimodal Dataset for Insect Biodiversity. CoRR abs/2406.12723 (2024) - [i86]Akshita Gupta, Aditya Arora, Sanath Narayan, Salman Khan, Fahad Shahbaz Khan, Graham W. Taylor:
Open-Vocabulary Temporal Action Localization using Multimodal Guidance. CoRR abs/2406.15556 (2024) - [i85]Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor, Thomas B. Moeslund:
Agglomerative Token Clustering. CoRR abs/2409.11923 (2024) - 2023
- [j19]Angus Galloway, Anna Golubeva, Mahmoud Salem, Mihai Nica, Yani A. Ioannou, Graham W. Taylor:
Bounding generalization error with input compression: An empirical study with infinite-width networks. Trans. Mach. Learn. Res. 2023 (2023) - [c83]Cong Wei, Brendan Duke, Ruowei Jiang, Parham Aarabi, Graham W. Taylor, Florian Shkurti:
Sparsifiner: Learning Sparse Instance-Dependent Attention for Efficient Vision Transformers. CVPR 2023: 22680-22689 - [c82]Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor, Thomas B. Moeslund:
Which Tokens to Use? Investigating Token Reduction in Vision Transformers. ICCV (Workshops) 2023: 773-783 - [c81]Mateusz Maria Jurewicz, Graham W. Taylor, Leon Derczynski:
The Catalog Problem: Clustering and Ordering Variable-Sized Sets. ICML 2023: 15528-15545 - [c80]Zahra Gharaee, ZeMing Gong, Nicholas Pellegrino, Iuliia Zarubiieva, Joakim Bruslund Haurum, Scott C. Lowe, Jaclyn T. A. McKeown, Chris C. Y. Ho, Joschka McLeod, Yi-Yun C. Wei, Jireh Agda, Sujeevan Ratnasingham, Dirk Steinke, Angel X. Chang, Graham W. Taylor, Paul W. Fieguth:
A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset. NeurIPS 2023 - [i84]Juan Carrasquilla, Mohamed Hibat-Allah, Estelle M. Inack, Alireza Makhzani, Kirill Neklyudov, Graham W. Taylor, Giacomo Torlai:
Quantum HyperNetworks: Training Binary Neural Networks in Quantum Superposition. CoRR abs/2301.08292 (2023) - [i83]Mingjie Wang, Yande Li, Jun Zhou, Graham W. Taylor, Minglun Gong:
GCNet: Probing Self-Similarity Learning for Generalized Counting Network. CoRR abs/2302.05132 (2023) - [i82]Cong Wei, Brendan Duke, Ruowei Jiang, Parham Aarabi, Graham W. Taylor, Florian Shkurti:
Sparsifiner: Learning Sparse Instance-Dependent Attention for Efficient Vision Transformers. CoRR abs/2303.13755 (2023) - [i81]Kevin Kasa, Graham W. Taylor:
Empirically Validating Conformal Prediction on Modern Vision Architectures Under Distribution Shift and Long-tailed Data. CoRR abs/2307.01088 (2023) - [i80]Zahra Gharaee, ZeMing Gong, Nicholas Pellegrino, Iuliia Zarubiieva, Joakim Bruslund Haurum, Scott C. Lowe, Jaclyn T. A. McKeown, Chris C. Y. Ho, Joschka McLeod, Yi-Yun C. Wei, Jireh Agda, Sujeevan Ratnasingham, Dirk Steinke, Angel X. Chang, Graham W. Taylor, Paul W. Fieguth:
A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset. CoRR abs/2307.10455 (2023) - [i79]Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor, Thomas B. Moeslund:
Which Tokens to Use? Investigating Token Reduction in Vision Transformers. CoRR abs/2308.04657 (2023) - [i78]Michal Lisicki, Mihai Nica, Graham W. Taylor:
Bandit-Driven Batch Selection for Robust Learning under Label Noise. CoRR abs/2311.00096 (2023) - [i77]Pablo Millan Arias, Niousha Sadjadi, Monireh Safari, ZeMing Gong, Austin T. Wang, Scott C. Lowe, Joakim Bruslund Haurum, Iuliia Zarubiieva, Dirk Steinke, Lila Kari, Angel X. Chang, Graham W. Taylor:
BarcodeBERT: Transformers for Biodiversity Analysis. CoRR abs/2311.02401 (2023) - [i76]C. Kupferschmidt, A. D. Binns, Kristina L. Kupferschmidt, Graham W. Taylor:
Stable Rivers: A Case Study in the Application of Text-to-Image Generative Models for Earth Sciences. CoRR abs/2312.07833 (2023) - 2022
- [c79]Kristina L. Kupferschmidt, Joshua August Gus Skorburg, Graham W. Taylor:
DelphAI: A human-centered approach to time-series forecasting. IEEE Big Data 2022: 4014-4020 - [c78]Eu Wern Teh, Terrance DeVries, Brendan Duke, Ruowei Jiang, Parham Aarabi, Graham W. Taylor:
The GIST and RIST of Iterative Self-Training for Semi-Supervised Segmentation. CRV 2022: 58-66 - [c77]Eu Wern Teh, Graham W. Taylor:
Understanding the impact of image and input resolution on deep digital pathology patch classifiers. CRV 2022: 159-166 - [c76]Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham W. Taylor:
On Evaluation Metrics for Graph Generative Models. ICLR 2022 - [c75]Eu Wern The, Graham W. Taylor:
Learning with Less Labels in Digital Pathology Via Scribble Supervision from Natural Images. ISBI 2022: 1-5 - [i75]Eu Wern Teh, Graham W. Taylor:
Learning with Less Labels in Digital Pathology via Scribble Supervision from Natural Images. CoRR abs/2201.02627 (2022) - [i74]Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham W. Taylor:
On Evaluation Metrics for Graph Generative Models. CoRR abs/2201.09871 (2022) - [i73]Chuan-Yung Tsai, Graham W. Taylor:
DeepRNG: Towards Deep Reinforcement Learning-Assisted Generative Testing of Software. CoRR abs/2201.12602 (2022) - [i72]Eu Wern Teh, Graham W. Taylor:
Understanding the impact of image and input resolution on deep digital pathology patch classifiers. CoRR abs/2204.13829 (2022) - [i71]Mohammed Adnan, Yani A. Ioannou, Chuan-Yung Tsai, Angus Galloway, Hamid R. Tizhoosh, Graham W. Taylor:
Monitoring Shortcut Learning using Mutual Information. CoRR abs/2206.13034 (2022) - [i70]Angus Galloway, Anna Golubeva, Mahmoud Salem, Mihai Nica, Yani A. Ioannou, Graham W. Taylor:
Bounding generalization error with input compression: An empirical study with infinite-width networks. CoRR abs/2207.09408 (2022) - 2021
- [j18]Chris Kim, Xiao Lin, Christopher Collins, Graham W. Taylor, Mohamed R. Amer:
Learn, Generate, Rank, Explain: A Case Study of Visual Explanation by Generative Machine Learning. ACM Trans. Interact. Intell. Syst. 11(3-4): 23:1-23:34 (2021) - [c74]Rohit Saha, Brendan Duke, Florian Shkurti, Graham W. Taylor, Parham Aarabi:
LOHO: Latent Optimization of Hairstyles via Orthogonalization. CVPR 2021: 1984-1993 - [c73]Brendan Duke, Abdalla Ahmed, Christian Wolf, Parham Aarabi, Graham W. Taylor:
SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation. CVPR 2021: 5912-5921 - [c72]Terrance DeVries, Miguel Ángel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind:
Unconstrained Scene Generation with Locally Conditioned Radiance Fields. ICCV 2021: 14284-14293 - [c71]Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky:
Generative Compositional Augmentations for Scene Graph Prediction. ICCV 2021: 15807-15817 - [c70]Yichao Lu, Himanshu Rai, Jason Chang, Boris Knyazev, Guang Wei Yu, Shashank Shekhar, Graham W. Taylor, Maksims Volkovs:
Context-aware Scene Graph Generation with Seq2Seq Transformers. ICCV 2021: 15911-15921 - [c69]Clair Baleshta, Dylan White, Glen Reavie, Alysha Cooper, Graham W. Taylor, Joshua August Gus Skorburg, David Van Bruwaene, Sarah Gignac, Chris Schmidt, Laura McDonald, Patricia Thaine, Chloë Ryan, Rency Luan:
CARE-AI special session on AI ethics. ISTAS 2021: 1-2 - [c68]Graham W. Taylor, Theresa Bernardo, Deborah Stacey, Kassy Raymond, Rozita Dara, Samira Yousefinaghani, Ethan Pike:
One Health Informatics and the stewardship of complex systems. ISTAS 2021: 1-2 - [c67]Hyunsoo Chung, Jungtaek Kim, Boris Knyazev, Jinhwi Lee, Graham W. Taylor, Jaesik Park, Minsu Cho:
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning. NeurIPS 2021: 5745-5757 - [c66]Boris Knyazev, Michal Drozdzal, Graham W. Taylor, Adriana Romero-Soriano:
Parameter Prediction for Unseen Deep Architectures. NeurIPS 2021: 29433-29448 - [i69]Brendan Duke, Abdalla Ahmed, Christian Wolf, Parham Aarabi, Graham W. Taylor:
SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation. CoRR abs/2101.08833 (2021) - [i68]Rohit Saha, Brendan Duke, Florian Shkurti, Graham W. Taylor, Parham Aarabi:
LOHO: Latent Optimization of Hairstyles via Orthogonalization. CoRR abs/2103.03891 (2021) - [i67]Eu Wern Teh, Terrance DeVries, Brendan Duke, Ruowei Jiang, Parham Aarabi, Graham W. Taylor:
The GIST and RIST of Iterative Self-Training for Semi-Supervised Segmentation. CoRR abs/2103.17105 (2021) - [i66]Terrance DeVries, Miguel Ángel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind:
Unconstrained Scene Generation with Locally Conditioned Radiance Fields. CoRR abs/2104.00670 (2021) - [i65]Boris Knyazev, Michal Drozdzal, Graham W. Taylor, Adriana Romero-Soriano:
Parameter Prediction for Unseen Deep Architectures. CoRR abs/2110.13100 (2021) - [i64]Hyunsoo Chung, Jungtaek Kim, Boris Knyazev, Jinhwi Lee, Graham W. Taylor, Jaesik Park, Minsu Cho:
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning. CoRR abs/2110.15481 (2021) - [i63]Michal Lisicki, Arash Afkanpour, Graham W. Taylor:
An Empirical Study of Neural Kernel Bandits. CoRR abs/2111.03543 (2021) - [i62]Mohammed Adnan, Yani A. Ioannou, Chuan-Yung Tsai, Graham W. Taylor:
Domain-Agnostic Clustering with Self-Distillation. CoRR abs/2111.12170 (2021) - 2020
- [j17]Ahmed Elshamli, Graham W. Taylor, Shawki Areibi:
Multisource Domain Adaptation for Remote Sensing Using Deep Neural Networks. IEEE Trans. Geosci. Remote. Sens. 58(5): 3328-3340 (2020) - [c65]Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky:
Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. BMVC 2020 - [c64]J. Eric Taylor, Shashank Shekhar, Graham W. Taylor:
Response Time Analysis for Explainability of Visual Processing in CNNs. CVPR Workshops 2020: 1555-1558 - [c63]Eu Wern Teh, Terrance DeVries, Graham W. Taylor:
ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis. ECCV (24) 2020: 448-464 - [c62]Shivam Kalra, Mohammed Adnan, Graham W. Taylor, Hamid R. Tizhoosh:
Learning Permutation Invariant Representations Using Memory Networks. ECCV (29) 2020: 677-693 - [c61]Katya Kudashkina, Peter Wittek, Jamie Kiros, Graham W. Taylor:
Modular Length Control for Sentence Generation. ESANN 2020: 607-612 - [c60]Vithursan Thangarasa, Thomas Miconi, Graham W. Taylor:
Enabling Continual Learning with Differentiable Hebbian Plasticity. IJCNN 2020: 1-8 - [c59]Eu Wern Teh, Graham W. Taylor:
Learning with Less Data Via Weakly Labeled Patch Classification in Digital Pathology. ISBI 2020: 471-475 - [c58]Terrance DeVries, Michal Drozdzal, Graham W. Taylor:
Instance Selection for GANs. NeurIPS 2020 - [c57]Stefan Schneider, Graham W. Taylor, Stefan C. Kremer:
Similarity Learning Networks for Animal Individual Re-Identification - Beyond the Capabilities of a Human Observer. WACV Workshops 2020: 44-52 - [i61]Eu Wern Teh, Terrance DeVries, Graham W. Taylor:
ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis. CoRR abs/2004.01113 (2020) - [i60]Katya Kudashkina, Valliappa Chockalingam, Graham W. Taylor, Michael Bowling:
Sample-Efficient Model-based Actor-Critic for an Interactive Dialogue Task. CoRR abs/2004.13657 (2020) - [i59]Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky:
Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. CoRR abs/2005.08230 (2020) - [i58]Vithursan Thangarasa, Thomas Miconi, Graham W. Taylor:
Enabling Continual Learning with Differentiable Hebbian Plasticity. CoRR abs/2006.16558 (2020) - [i57]Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky:
Generative Graph Perturbations for Scene Graph Prediction. CoRR abs/2007.05756 (2020) - [i56]Terrance DeVries, Michal Drozdzal, Graham W. Taylor:
Instance Selection for GANs. CoRR abs/2007.15255 (2020) - [i55]Nolan S. Dey, J. Eric Taylor, Bryan P. Tripp, Alexander Wong, Graham W. Taylor:
Identifying and interpreting tuning dimensions in deep networks. CoRR abs/2011.03043 (2020) - [i54]Michal Lisicki, Arash Afkanpour, Graham W. Taylor:
Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization. CoRR abs/2011.06188 (2020) - [i53]Rylee Thompson, Elahe Ghalebi, Terrance DeVries, Graham W. Taylor:
Building LEGO Using Deep Generative Models of Graphs. CoRR abs/2012.11543 (2020)
2010 – 2019
- 2019
- [j16]Devinder Kumar, Graham W. Taylor, Alexander Wong:
Discovery Radiomics With CLEAR-DR: Interpretable Computer Aided Diagnosis of Diabetic Retinopathy. IEEE Access 7: 25891-25896 (2019) - [j15]Devinder Kumar, Vignesh Sankar, David A. Clausi, Graham W. Taylor, Alexander Wong:
SISC: End-to-End Interpretable Discovery Radiomics-Driven Lung Cancer Prediction via Stacked Interpretable Sequencing Cells. IEEE Access 7: 145444-145454 (2019) - [c56]Boris Knyazev, Xiao Lin, Mohamed R. Amer, Graham W. Taylor:
Image Classification with Hierarchical Multigraph Networks. BMVC 2019: 251 - [c55]Eu Wern Teh, Graham W. Taylor:
Apparent Age Estimation with Relational Networks. CRV 2019: 89-96 - [c54]Devinder Kumar, Ibrahim Ben Daya, Kanav Vats, Jeffery Feng, Graham W. Taylor, Alexander Wong:
Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning. CVPR Workshops 2019: 16-19 - [c53]Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz, R. Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio, Graham W. Taylor:
Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction. ICCV 2019: 10303-10311 - [c52]Boris Knyazev, Graham W. Taylor, Mohamed R. Amer:
Understanding Attention and Generalization in Graph Neural Networks. NeurIPS 2019: 4204-4214 - [c51]Nihal Murali, Jon Schneider, Joel Levine, Graham W. Taylor:
Classification and Re-Identification of Fruit Fly Individuals Across Days With Convolutional Neural Networks. WACV 2019: 570-578 - [i52]Vignesh Sankar, Devinder Kumar, David A. Clausi, Graham W. Taylor, Alexander Wong:
SISC: End-to-end Interpretable Discovery Radiomics-Driven Lung Cancer Prediction via Stacked Interpretable Sequencing Cells. CoRR abs/1901.04641 (2019) - [i51]Stefan Schneider, Graham W. Taylor, Stefan S. Linquist, Stefan C. Kremer:
Similarity Learning Networks for Animal Individual Re-Identification - Beyond the Capabilities of a Human Observer. CoRR abs/1902.09324 (2019) - [i50]Devinder Kumar, Ibrahim Ben Daya, Kanav Vats, Jeffery Feng, Graham W. Taylor, Alexander Wong:
Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning. CoRR abs/1904.09633 (2019) - [i49]Angus Galloway, Anna Golubeva, Thomas Tanay, Medhat Moussa, Graham W. Taylor:
Batch Normalization is a Cause of Adversarial Vulnerability. CoRR abs/1905.02161 (2019) - [i48]Boris Knyazev, Graham W. Taylor, Mohamed R. Amer:
Understanding attention in graph neural networks. CoRR abs/1905.02850 (2019) - [i47]Terrance DeVries, Adriana Romero, Luis Pineda, Graham W. Taylor, Michal Drozdzal:
On the Evaluation of Conditional GANs. CoRR abs/1907.08175 (2019) - [i46]Boris Knyazev, Xiao Lin, Mohamed R. Amer, Graham W. Taylor:
Image Classification with Hierarchical Multigraph Networks. CoRR abs/1907.09000 (2019) - [i45]Boris Knyazev, Carolyn Augusta, Graham W. Taylor:
Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions. CoRR abs/1909.10367 (2019) - [i44]Elahe Ghalebi, Hamidreza Mahyar, Radu Grosu, Graham W. Taylor, Sinead A. Williamson:
A Nonparametric Bayesian Model for Sparse Temporal Multigraphs. CoRR abs/1910.05098 (2019) - [i43]Alaaeldin El-Nouby, Shuangfei Zhai, Graham W. Taylor, Joshua M. Susskind:
Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking. CoRR abs/1910.12770 (2019) - [i42]Shivam Kalra, Mohammed Adnan, Graham W. Taylor, Hamid R. Tizhoosh:
Learning Permutation Invariant Representations using Memory Networks. CoRR abs/1911.07984 (2019) - [i41]Eu Wern Teh, Graham W. Taylor:
Learning with less data via Weakly Labeled Patch Classification in Digital Pathology. CoRR abs/1911.12425 (2019) - 2018
- [j14]Colin Brennan, Graham W. Taylor, Petros Spachos:
Designing learned CO2-based occupancy estimation in smart buildings. IET Wirel. Sens. Syst. 8(6): 249-255 (2018) - [j13]Dhanesh Ramachandram, Michal Lisicki, Timothy J. Shields, Mohamed R. Amer, Graham W. Taylor:
Bayesian optimization on graph-structured search spaces: Optimizing deep multimodal fusion architectures. Neurocomputing 298: 80-89 (2018) - [c50]Vithursan Thangarasa, Graham W. Taylor:
Self-Paced Learning with Adaptive Deep Visual Embeddings. BMVC 2018: 276 - [c49]Alaaeldin El-Nouby, Graham W. Taylor:
Real-Time End-to-End Action Detection with Two-Stream Networks. CRV 2018: 31-38 - [c48]Brendan Duke, Graham W. Taylor:
Generalized Hadamard-Product Fusion Operators for Visual Question Answering. CRV 2018: 39-46 - [c47]Stefan Schneider, Graham W. Taylor, Stefan C. Kremer:
Deep Learning Object Detection Methods for Ecological Camera Trap Data. CRV 2018: 321-328 - [c46]Shamak Dutta, Bryan P. Tripp, Graham W. Taylor:
Convolutional Neural Networks Regularized by Correlated Noise. CRV 2018: 375-382 - [c45]Fabien Baradel, Christian Wolf, Julien Mille, Graham W. Taylor:
Glimpse Clouds: Human Activity Recognition From Unstructured Feature Points. CVPR 2018: 469-478 - [c44]Angus Galloway, Graham W. Taylor, Medhat Moussa:
Attacking Binarized Neural Networks. ICLR (Poster) 2018 - [c43]Daniel Jiwoong Im, He Ma, Graham W. Taylor, Kristin Branson:
Quantitatively Evaluating GANs With Divergences Proposed for Training. ICLR (Poster) 2018 - [c42]Devinder Kumar, Vlado Menkovski, Graham W. Taylor, Alexander Wong:
Understanding anatomy classification through attentive response maps. ISBI 2018: 1130-1133 - [c41]Colin Brennan, Graham W. Taylor, Petros Spachos:
Distributed Sensor Network for Indirect Occupancy Measurement in Smart Buildings. IWCMC 2018: 1290-1295 - [c40]Brad Kennedy, Graham W. Taylor, Petros Spachos:
BLE Beacon Based Patient Tracking in Smart Care Facilities. PerCom Workshops 2018: 439-441 - [c39]Griffin Lacey, Graham W. Taylor, Shawki Areibi:
Stochastic Layer-Wise Precision in Deep Neural Networks. UAI 2018: 663-672 - [i40]Angus Galloway, Graham W. Taylor, Medhat Moussa:
Predicting Adversarial Examples with High Confidence. CoRR abs/1802.04457 (2018) - [i39]Terrance DeVries, Graham W. Taylor:
Learning Confidence for Out-of-Distribution Detection in Neural Networks. CoRR abs/1802.04865 (2018) - [i38]Fabien Baradel, Christian Wolf, Julien Mille, Graham W. Taylor:
Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points. CoRR abs/1802.07898 (2018) - [i37]Alaaeldin El-Nouby, Graham W. Taylor:
Real-Time End-to-End Action Detection with Two-Stream Networks. CoRR abs/1802.08362 (2018) - [i36]Daniel Jiwoong Im, He Ma, Graham W. Taylor, Kristin Branson:
Quantitatively Evaluating GANs With Divergences Proposed for Training. CoRR abs/1803.01045 (2018) - [i35]Brendan Duke, Graham W. Taylor:
Generalized Hadamard-Product Fusion Operators for Visual Question Answering. CoRR abs/1803.09374 (2018) - [i34]Stefan Schneider, Graham W. Taylor, Stefan C. Kremer:
Deep Learning Object Detection Methods for Ecological Camera Trap Data. CoRR abs/1803.10842 (2018) - [i33]Shamak Dutta, Bryan P. Tripp, Graham W. Taylor:
Convolutional Neural Networks Regularized by Correlated Noise. CoRR abs/1804.00815 (2018) - [i32]Angus Galloway, Thomas Tanay, Graham W. Taylor:
Adversarial Training Versus Weight Decay. CoRR abs/1804.03308 (2018) - [i31]Terrance DeVries, Graham W. Taylor:
Leveraging Uncertainty Estimates for Predicting Segmentation Quality. CoRR abs/1807.00502 (2018) - [i30]Griffin Lacey, Graham W. Taylor, Shawki Areibi:
Stochastic Layer-Wise Precision in Deep Neural Networks. CoRR abs/1807.00942 (2018) - [i29]Vithursan Thangarasa, Graham W. Taylor:
Self-Paced Learning with Adaptive Deep Visual Embeddings. CoRR abs/1807.09200 (2018) - [i28]Stefan Schneider, Graham W. Taylor, Stefan S. Linquist, Stefan C. Kremer:
Past, Present, and Future Approaches Using Computer Vision for Animal Re-Identification from Camera Trap Data. CoRR abs/1811.07749 (2018) - [i27]Boris Knyazev, Xiao Lin, Mohamed R. Amer, Graham W. Taylor:
Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules. CoRR abs/1811.09595 (2018) - [i26]Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz, R. Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio, Graham W. Taylor:
Keep Drawing It: Iterative language-based image generation and editing. CoRR abs/1811.09845 (2018) - [i25]Angus Galloway, Anna Golubeva, Graham W. Taylor:
Adversarial Examples as an Input-Fault Tolerance Problem. CoRR abs/1811.12601 (2018) - 2017
- [j12]Natalia Neverova, Christian Wolf, Florian Nebout, Graham W. Taylor:
Hand pose estimation through semi-supervised and weakly-supervised learning. Comput. Vis. Image Underst. 164: 56-67 (2017) - [j11]