Graham W. Taylor

According to our database, Graham W. Taylor authored at least 143 papers between 2004 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Bounding generalization error with input compression: An empirical study with infinite-width networks.

Angus Galloway, Anna Golubeva, Mahmoud Salem, Mihai Nica, Yani A. Ioannou, Graham W. Taylor

Trans. Mach. Learn. Res., 2023

Stable Rivers: A Case Study in the Application of Text-to-Image Generative Models for Earth Sciences.

C. Kupferschmidt, A. D. Binns, Kristina L. Kupferschmidt, Graham W. Taylor

CoRR, 2023

BarcodeBERT: Transformers for Biodiversity Analysis.

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

CoRR, 2023

Bandit-Driven Batch Selection for Robust Learning under Label Noise.

Michal Lisicki, Mihai Nica, Graham W. Taylor

CoRR, 2023

Empirically Validating Conformal Prediction on Modern Vision Architectures Under Distribution Shift and Long-tailed Data.

Kevin Kasa, Graham W. Taylor

CoRR, 2023

GCNet: Probing Self-Similarity Learning for Generalized Counting Network.

Mingjie Wang, Yande Li, Jun Zhou, Graham W. Taylor, Minglun Gong

CoRR, 2023

Quantum HyperNetworks: Training Binary Neural Networks in Quantum Superposition.

Juan Carrasquilla, Mohamed Hibat-Allah, Estelle M. Inack, Alireza Makhzani, Kirill Neklyudov, Graham W. Taylor, Giacomo Torlai

CoRR, 2023

A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Catalog Problem: Clustering and Ordering Variable-Sized Sets.

Mateusz Maria Jurewicz, Graham W. Taylor, Leon Derczynski

Proceedings of the International Conference on Machine Learning, 2023

Which Tokens to Use? Investigating Token Reduction in Vision Transformers.

Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor, Thomas B. Moeslund

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Sparsifiner: Learning Sparse Instance-Dependent Attention for Efficient Vision Transformers.

Cong Wei, Brendan Duke, Ruowei Jiang, Parham Aarabi, Graham W. Taylor, Florian Shkurti

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Monitoring Shortcut Learning using Mutual Information.

Mohammed Adnan, Yani A. Ioannou, Chuan-Yung Tsai, Angus Galloway, Hamid R. Tizhoosh, Graham W. Taylor

CoRR, 2022

DeepRNG: Towards Deep Reinforcement Learning-Assisted Generative Testing of Software.

Chuan-Yung Tsai, Graham W. Taylor

CoRR, 2022

Learning with Less Labels in Digital Pathology via Scribble Supervision from Natural Images.

Eu Wern Teh, Graham W. Taylor

CoRR, 2022

Learning with Less Labels in Digital Pathology Via Scribble Supervision from Natural Images.

Eu Wern The, Graham W. Taylor

Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

On Evaluation Metrics for Graph Generative Models.

Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham W. Taylor

Proceedings of the Tenth International Conference on Learning Representations, 2022

Understanding the impact of image and input resolution on deep digital pathology patch classifiers.

Eu Wern Teh, Graham W. Taylor

Proceedings of the 19th Conference on Robots and Vision, 2022

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

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

Proceedings of the 19th Conference on Robots and Vision, 2022

DelphAI: A human-centered approach to time-series forecasting.

Kristina L. Kupferschmidt, Joshua August Gus Skorburg, Graham W. Taylor

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Learn, Generate, Rank, Explain: A Case Study of Visual Explanation by Generative Machine Learning.

Chris Kim, Xiao Lin, Christopher Collins, Graham W. Taylor, Mohamed R. Amer

ACM Trans. Interact. Intell. Syst., 2021

Domain-Agnostic Clustering with Self-Distillation.

Mohammed Adnan, Yani A. Ioannou, Chuan-Yung Tsai, Graham W. Taylor

CoRR, 2021

An Empirical Study of Neural Kernel Bandits.

Michal Lisicki, Arash Afkanpour, Graham W. Taylor

CoRR, 2021

Parameter Prediction for Unseen Deep Architectures.

Boris Knyazev, Michal Drozdzal, Graham W. Taylor, Adriana Romero-Soriano

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning.

Hyunsoo Chung, Jungtaek Kim, Boris Knyazev, Jinhwi Lee, Graham W. Taylor, Jaesik Park, Minsu Cho

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

One Health Informatics and the stewardship of complex systems.

Graham W. Taylor, Theresa Bernardo, Deborah Stacey, Kassy Raymond, Rozita Dara, Samira Yousefinaghani, Ethan Pike

Proceedings of the IEEE International Symposium on Technology and Society, 2021

CARE-AI special session on AI ethics.

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

Proceedings of the IEEE International Symposium on Technology and Society, 2021

Context-aware Scene Graph Generation with Seq2Seq Transformers.

Yichao Lu, Himanshu Rai, Jason Chang, Boris Knyazev, Guang Wei Yu, Shashank Shekhar, Graham W. Taylor, Maksims Volkovs

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Generative Compositional Augmentations for Scene Graph Prediction.

Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Unconstrained Scene Generation with Locally Conditioned Radiance Fields.

Terrance DeVries, Miguel Ángel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

LOHO: Latent Optimization of Hairstyles via Orthogonalization.

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

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation.

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

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Multisource Domain Adaptation for Remote Sensing Using Deep Neural Networks.

Ahmed Elshamli, Graham W. Taylor, Shawki Areibi

IEEE Trans. Geosci. Remote. Sens., 2020

Building LEGO Using Deep Generative Models of Graphs.

Rylee Thompson, Elahe Ghalebi, Terrance DeVries, Graham W. Taylor

CoRR, 2020

Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization.

Michal Lisicki, Arash Afkanpour, Graham W. Taylor

CoRR, 2020

Identifying and interpreting tuning dimensions in deep networks.

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

CoRR, 2020

Generative Graph Perturbations for Scene Graph Prediction.

Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky

CoRR, 2020

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

Katya Kudashkina, Valliappa Chockalingam, Graham W. Taylor, Michael Bowling

CoRR, 2020

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

Stefan Schneider, Graham W. Taylor, Stefan C. Kremer

Proceedings of the IEEE Winter Applications of Computer Vision Workshops, 2020

Instance Selection for GANs.

Terrance DeVries, Michal Drozdzal, Graham W. Taylor

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning with Less Data Via Weakly Labeled Patch Classification in Digital Pathology.

Eu Wern Teh, Graham W. Taylor

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Enabling Continual Learning with Differentiable Hebbian Plasticity.

Vithursan Thangarasa, Thomas Miconi, Graham W. Taylor

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Modular Length Control for Sentence Generation.

Katya Kudashkina, Peter Wittek, Jamie Kiros, Graham W. Taylor

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis.

Eu Wern Teh, Terrance DeVries, Graham W. Taylor

Proceedings of the Computer Vision - ECCV 2020, 2020

Learning Permutation Invariant Representations Using Memory Networks.

Shivam Kalra, Mohammed Adnan, Graham W. Taylor, Hamid R. Tizhoosh

Proceedings of the Computer Vision - ECCV 2020, 2020

Response Time Analysis for Explainability of Visual Processing in CNNs.

J. Eric Taylor, Shashank Shekhar, Graham W. Taylor

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

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

Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky

Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019

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

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

CoRR, 2019

A Nonparametric Bayesian Model for Sparse Temporal Multigraphs.

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

CoRR, 2019

Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions.

Boris Knyazev, Carolyn Augusta, Graham W. Taylor

CoRR, 2019

On the Evaluation of Conditional GANs.

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

CoRR, 2019

Understanding attention in graph neural networks.

Boris Knyazev, Graham W. Taylor, Mohamed R. Amer

CoRR, 2019

Batch Normalization is a Cause of Adversarial Vulnerability.

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

CoRR, 2019

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

Stefan Schneider, Graham W. Taylor, Stefan S. Linquist, Stefan C. Kremer

CoRR, 2019

Discovery Radiomics With CLEAR-DR: Interpretable Computer Aided Diagnosis of Diabetic Retinopathy.

Devinder Kumar, Graham W. Taylor, Alexander Wong

IEEE Access, 2019

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

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

IEEE Access, 2019

Classification and Re-Identification of Fruit Fly Individuals Across Days With Convolutional Neural Networks.

Nihal Murali, Jon Schneider, Joel Levine, Graham W. Taylor

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

Understanding Attention and Generalization in Graph Neural Networks.

Boris Knyazev, Graham W. Taylor, Mohamed R. Amer

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction.

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

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning.

Devinder Kumar, Ibrahim Ben Daya, Kanav Vats, Jeffery Feng, Graham W. Taylor, Alexander Wong

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Apparent Age Estimation with Relational Networks.

Eu Wern Teh, Graham W. Taylor

Proceedings of the 16th Conference on Computer and Robot Vision, 2019

Image Classification with Hierarchical Multigraph Networks.

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

Proceedings of the 30th British Machine Vision Conference 2019, 2019

2018

Bayesian optimization on graph-structured search spaces: Optimizing deep multimodal fusion architectures.

Dhanesh Ramachandram, Michal Lisicki, Timothy J. Shields, Mohamed R. Amer, Graham W. Taylor

Neurocomputing, 2018

Designing learned CO₂-based occupancy estimation in smart buildings.

Colin Brennan, Graham W. Taylor, Petros Spachos

IET Wirel. Sens. Syst., 2018

Adversarial Examples as an Input-Fault Tolerance Problem.

Angus Galloway, Anna Golubeva, Graham W. Taylor

CoRR, 2018

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

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

CoRR, 2018

Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules.

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

CoRR, 2018

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

Stefan Schneider, Graham W. Taylor, Stefan S. Linquist, Stefan C. Kremer

CoRR, 2018

Leveraging Uncertainty Estimates for Predicting Segmentation Quality.

Terrance DeVries, Graham W. Taylor

CoRR, 2018

Adversarial Training Versus Weight Decay.

Angus Galloway, Thomas Tanay, Graham W. Taylor

CoRR, 2018

Learning Confidence for Out-of-Distribution Detection in Neural Networks.

Terrance DeVries, Graham W. Taylor

CoRR, 2018

Predicting Adversarial Examples with High Confidence.

Angus Galloway, Graham W. Taylor, Medhat Moussa

CoRR, 2018

Stochastic Layer-Wise Precision in Deep Neural Networks.

Griffin Lacey, Graham W. Taylor, Shawki Areibi

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

BLE Beacon Based Patient Tracking in Smart Care Facilities.

Brad Kennedy, Graham W. Taylor, Petros Spachos

Proceedings of the 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, 2018

Distributed Sensor Network for Indirect Occupancy Measurement in Smart Buildings.

Colin Brennan, Graham W. Taylor, Petros Spachos

Proceedings of the 14th International Wireless Communications & Mobile Computing Conference, 2018

Understanding anatomy classification through attentive response maps.

Devinder Kumar, Vlado Menkovski, Graham W. Taylor, Alexander Wong

Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Quantitatively Evaluating GANs With Divergences Proposed for Training.

Daniel Jiwoong Im, He Ma, Graham W. Taylor, Kristin Branson

Proceedings of the 6th International Conference on Learning Representations, 2018

Attacking Binarized Neural Networks.

Angus Galloway, Graham W. Taylor, Medhat Moussa

Proceedings of the 6th International Conference on Learning Representations, 2018

Glimpse Clouds: Human Activity Recognition From Unstructured Feature Points.

Fabien Baradel, Christian Wolf, Julien Mille, Graham W. Taylor

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Deep Learning Object Detection Methods for Ecological Camera Trap Data.

Stefan Schneider, Graham W. Taylor, Stefan C. Kremer

Proceedings of the 15th Conference on Computer and Robot Vision, 2018

Convolutional Neural Networks Regularized by Correlated Noise.

Shamak Dutta, Bryan P. Tripp, Graham W. Taylor

Proceedings of the 15th Conference on Computer and Robot Vision, 2018

Generalized Hadamard-Product Fusion Operators for Visual Question Answering.

Brendan Duke, Graham W. Taylor

Proceedings of the 15th Conference on Computer and Robot Vision, 2018

Real-Time End-to-End Action Detection with Two-Stream Networks.

Alaaeldin El-Nouby, Graham W. Taylor

Proceedings of the 15th Conference on Computer and Robot Vision, 2018

Self-Paced Learning with Adaptive Deep Visual Embeddings.

Vithursan Thangarasa, Graham W. Taylor

Proceedings of the British Machine Vision Conference 2018, 2018

2017

Domain Adaptation Using Representation Learning for the Classification of Remote Sensing Images.

Ahmed Elshamli, Graham W. Taylor, Aaron Berg, Shawki Areibi

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017

Deep Multimodal Learning: A Survey on Recent Advances and Trends.

Dhanesh Ramachandram, Graham W. Taylor

IEEE Signal Process. Mag., 2017

Modeling Grasp Motor Imagery Through Deep Conditional Generative Models.

Matthew Veres, Medhat Moussa, Graham W. Taylor

IEEE Robotics Autom. Lett., 2017

Hand pose estimation through semi-supervised and weakly-supervised learning.

Natalia Neverova, Christian Wolf, Florian Nebout, Graham W. Taylor

Comput. Vis. Image Underst., 2017

Opening the Black Box of Financial AI with CLEAR-Trade: A CLass-Enhanced Attentive Response Approach for Explaining and Visualizing Deep Learning-Driven Stock Market Prediction.

Devinder Kumar, Graham W. Taylor, Alexander Wong

CoRR, 2017

Improved Regularization of Convolutional Neural Networks with Cutout.

Terrance Devries, Graham W. Taylor

CoRR, 2017

An Integrated Simulator and Dataset that Combines Grasping and Vision for Deep Learning.

Matthew Veres, Medhat A. Moussa, Graham W. Taylor

CoRR, 2017

Dataset Augmentation in Feature Space.

Terrance DeVries, Graham W. Taylor

Proceedings of the 5th International Conference on Learning Representations, 2017

Modout: Learning Multi-Modal Architectures by Stochastic Regularization.

Fan Li, Natalia Neverova, Christian Wolf, Graham W. Taylor

Proceedings of the 12th IEEE International Conference on Automatic Face & Gesture Recognition, 2017

Structure optimization for deep multimodal fusion networks using graph-induced kernels.

Dhanesh Ramachandram, Michal Lisicki, Timothy J. Shields, Mohamed R. Amer, Graham W. Taylor

Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Explaining the Unexplained: A CLass-Enhanced Attentive Response (CLEAR) Approach to Understanding Deep Neural Networks.

Devinder Kumar, Alexander Wong, Graham W. Taylor

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017

The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment.

Angus Galloway, Graham W. Taylor, Aaron Ramsay, Medhat Moussa

Proceedings of the 14th Conference on Computer and Robot Vision, 2017

2016

ModDrop: Adaptive Multi-Modal Gesture Recognition.

Natalia Neverova, Christian Wolf, Graham W. Taylor, Florian Nebout

IEEE Trans. Pattern Anal. Mach. Intell., 2016

Deep Learning on FPGAs: Past, Present, and Future.

Griffin Lacey, Graham W. Taylor, Shawki Areibi

CoRR, 2016

Generative Adversarial Parallelization.

Daniel Jiwoong Im, He Ma, Chris Dongjoo Kim, Graham W. Taylor

CoRR, 2016

Automatic moth detection from trap images for pest management.

Weiguang Ding, Graham W. Taylor

Comput. Electron. Agric., 2016

Learning Human Identity From Motion Patterns.

Natalia Neverova, Christian Wolf, Griffin Lacey, Lex Fridman, Deepak Chandra, Brandon Barbello, Graham W. Taylor

IEEE Access, 2016

Learning a metric for class-conditional KNN.

Daniel Jiwoong Im, Graham W. Taylor

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Caffeinated FPGAs: FPGA framework For Convolutional Neural Networks.

Roberto DiCecco, Griffin Lacey, Jasmina Vasiljevic, Paul Chow, Graham W. Taylor, Shawki Areibi

Proceedings of the 2016 International Conference on Field-Programmable Technology, 2016

Theano-MPI: A Theano-Based Distributed Training Framework.

He Ma, Fei Mao, Graham W. Taylor

Proceedings of the Euro-Par 2016: Parallel Processing Workshops, 2016

2015

Semisupervised Hyperspectral Image Classification via Neighborhood Graph Learning.

Daniel Jiwoong Im, Graham W. Taylor

IEEE Geosci. Remote. Sens. Lett., 2015

Generative Class-conditional Autoencoders.

Jan Rudy, Graham W. Taylor

Proceedings of the 3rd International Conference on Learning Representations, 2015

Learning with hidden variables.

Yasser Roudi, Graham W. Taylor

CoRR, 2015

Hand Pose Estimation through Weakly-Supervised Learning of a Rich Intermediate Representation.

Natalia Neverova, Christian Wolf, Florian Nebout, Graham W. Taylor

CoRR, 2015

Understanding Minimum Probability Flow for RBMs Under Various Kinds of Dynamics.

Daniel Jiwoong Im, Ethan Buchman, Graham W. Taylor

Proceedings of the 3rd International Conference on Learning Representations, 2015

Theano-based Large-Scale Visual Recognition with Multiple GPUs.

Weiguang Ding, Ruoyan Wang, Fei Mao, Graham W. Taylor

Proceedings of the 3rd International Conference on Learning Representations, 2015

Scoring and Classifying with Gated Auto-Encoders.

Daniel Jiwoong Im, Graham W. Taylor

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

An Empirical Investigation of Minimum Probability Flow Learning Under Different Connectivity Patterns.

Daniel Jiwoong Im, Ethan Buchman, Graham W. Taylor

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Deep Learning Architectures for Soil Property Prediction.

Matthew Veres, Griffin Lacey, Graham W. Taylor

Proceedings of the 12th Conference on Computer and Robot Vision, 2015

An Integrated System for Mapping Red Clover Ground Cover Using Unmanned Aerial Vehicles: A Case Study in Precision Agriculture.

Ammar M. Abuleil, Graham W. Taylor, Medhat Moussa

Proceedings of the 12th Conference on Computer and Robot Vision, 2015

2014

Human body part estimation from depth images via spatially-constrained deep learning.

Mingyuan Jiu, Christian Wolf, Graham W. Taylor, Atilla Baskurt

Pattern Recognit. Lett., 2014

Neural Network Regularization via Robust Weight Factorization.

Jan Rudy, Weiguang Ding, Daniel Jiwoong Im, Graham W. Taylor

CoRR, 2014

Learning Human Pose Estimation Features with Convolutional Networks.

Arjun Jain, Jonathan Tompson, Mykhaylo Andriluka, Graham W. Taylor, Christoph Bregler

Proceedings of the 2nd International Conference on Learning Representations, 2014

"Mental Rotation" by Optimizing Transforming Distance.

Weiguang Ding, Graham W. Taylor

CoRR, 2014

Multi-scale Deep Learning for Gesture Detection and Localization.

Natalia Neverova, Christian Wolf, Graham W. Taylor, Florian Nebout

Proceedings of the Computer Vision - ECCV 2014 Workshops, 2014

Multi-task Learning of Facial Landmarks and Expression.

Terrance Devries, Kumar Biswaranjan, Graham W. Taylor

Proceedings of the Canadian Conference on Computer and Robot Vision, 2014

Hand Segmentation with Structured Convolutional Learning.

Natalia Neverova, Christian Wolf, Graham W. Taylor, Florian Nebout

Proceedings of the Computer Vision - ACCV 2014, 2014

2013

A Multi-scale Approach to Gesture Detection and Recognition.

Natalia Neverova, Christian Wolf, Giulio Paci, Giacomo Sommavilla, Graham W. Taylor, Florian Nebout

Proceedings of the 2013 IEEE International Conference on Computer Vision Workshops, 2013

2012

Analysis of the IJCNN 2011 UTL challenge.

Isabelle Guyon, Gideon Dror, Vincent Lemaire, Daniel L. Silver, Graham W. Taylor, David W. Aha

Neural Networks, 2012

ICML2011 Unsupervised and Transfer Learning Workshop.

Daniel L. Silver, Isabelle Guyon, Graham W. Taylor, Gideon Dror, Vincent Lemaire

Proceedings of the Unsupervised and Transfer Learning, 2012

3D skeletal reconstruction from low-resolution multi-view images.

Mayank Rana, Graham W. Taylor, Ian Spiro, Christoph Bregler

Proceedings of the 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2012

2011

Two Distributed-State Models For Generating High-Dimensional Time Series.

Graham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis

J. Mach. Learn. Res., 2011

Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines.

Matthew D. Zeiler, Graham W. Taylor, Leonid Sigal, Iain A. Matthews, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Unsupervised and transfer learning challenge.

Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham W. Taylor, David W. Aha

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Adaptive deconvolutional networks for mid and high level feature learning.

Matthew D. Zeiler, Graham W. Taylor, Rob Fergus

Proceedings of the IEEE International Conference on Computer Vision, 2011

Learning invariance through imitation.

Graham W. Taylor, Ian Spiro, Christoph Bregler, Rob Fergus

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010

Composable, Distributed-state Models for High-dimensional Time Series.

Graham W. Taylor

PhD thesis, 2010

Pose-Sensitive Embedding by Nonlinear NCA Regression.

Graham W. Taylor, Rob Fergus, George Williams, Ian Spiro, Christoph Bregler

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Body Motion Analysis for Multi-modal Identity Verification.

George Williams, Graham W. Taylor, Kirill Smolskiy, Christoph Bregler

Proceedings of the 20th International Conference on Pattern Recognition, 2010

Convolutional Learning of Spatio-temporal Features.

Graham W. Taylor, Rob Fergus, Yann LeCun, Christoph Bregler

Proceedings of the Computer Vision - ECCV 2010, 2010

Deconvolutional networks.

Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylor, Robert Fergus

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Dynamical binary latent variable models for 3D human pose tracking.

Graham W. Taylor, Leonid Sigal, David J. Fleet, Geoffrey E. Hinton

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009

Products of Hidden Markov Models: It Takes N>1 to Tango.

Graham W. Taylor, Geoffrey E. Hinton

Proceedings of the UAI 2009, 2009

Factored conditional restricted Boltzmann Machines for modeling motion style.

Graham W. Taylor, Geoffrey E. Hinton

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Modeling pigeon behavior using a Conditional Restricted Boltzmann Machine.

Matthew D. Zeiler, Graham W. Taylor, Nikolaus F. Troje, Geoffrey E. Hinton

Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

2008

The Recurrent Temporal Restricted Boltzmann Machine.

Ilya Sutskever, Geoffrey E. Hinton, Graham W. Taylor

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Maximum a posteriori ICA: Applying prior knowledge to the separation of acoustic sources.

Graham W. Taylor, Michael L. Seltzer, Alex Acero

Proceedings of the IEEE International Conference on Acoustics, 2008

2006

Reinforced Contrast Adaptation.

Hamid R. Tizhoosh, Graham W. Taylor

Int. J. Image Graph., 2006

Modeling Human Motion Using Binary Latent Variables.

Graham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2004

A Reinforcement Learning Framework for Parameter Control in Computer Vision Applications.

Graham W. Taylor

Proceedings of the 1st Canadian Conference on Computer and Robot Vision (CRV 2004) 17-19 May 2004, 2004