A Reinforcement Learning Framework for Parameter Control in Computer Vision Applications. - Graham W. Taylor (CRV, 2004)

Modeling Human Motion Using Binary Latent Variables. - Graham W. Taylor; Geoffrey E. Hinton; Sam T. Roweis (NIPS, 2006)

Reinforced Contrast Adaptation. - Hamid R. Tizhoosh; Graham W. Taylor (Int. J. Image Graph., 2006)

Maximum a posteriori ICA: Applying prior knowledge to the separation of acoustic sources. - Graham W. Taylor; Michael L. Seltzer; Alex Acero (ICASSP, 2008)

The Recurrent Temporal Restricted Boltzmann Machine. - Ilya Sutskever; Geoffrey E. Hinton; Graham W. Taylor (NIPS, 2008)

Modeling pigeon behavior using a Conditional Restricted Boltzmann Machine. - Matthew D. Zeiler; Graham W. Taylor; Nikolaus F. Troje; Geoffrey E. Hinton (ESANN, 2009)

Factored conditional restricted Boltzmann Machines for modeling motion style. - Graham W. Taylor; Geoffrey E. Hinton (ICML, 2009)

Products of Hidden Markov Models: It Takes N>1 to Tango. - Graham W. Taylor; Geoffrey E. Hinton (UAI, 2009)

Dynamical binary latent variable models for 3D human pose tracking. - Graham W. Taylor; Leonid Sigal; David J. Fleet; Geoffrey E. Hinton (CVPR, 2010)

Deconvolutional networks. - Matthew D. Zeiler; Dilip Krishnan; Graham W. Taylor; Robert Fergus (CVPR, 2010)

Convolutional Learning of Spatio-temporal Features. - Graham W. Taylor; Rob Fergus; Yann LeCun; Christoph Bregler (ECCV (6), 2010)

Body Motion Analysis for Multi-modal Identity Verification. - George Williams; Graham W. Taylor; Kirill Smolskiy; Christoph Bregler (ICPR, 2010)

Pose-Sensitive Embedding by Nonlinear NCA Regression. - Graham W. Taylor; Rob Fergus; George Williams; Ian Spiro; Christoph Bregler (NIPS, 2010)

Composable, Distributed-state Models for High-dimensional Time Series. - Graham W. Taylor (2010)

Learning invariance through imitation. - Graham W. Taylor; Ian Spiro; Christoph Bregler; Rob Fergus (CVPR, 2011)

Adaptive deconvolutional networks for mid and high level feature learning. - Matthew D. Zeiler; Graham W. Taylor; Rob Fergus (ICCV, 2011)

Unsupervised and transfer learning challenge. - Isabelle Guyon; Gideon Dror; Vincent Lemaire 001; Graham W. Taylor; David W. Aha (IJCNN, 2011)

Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines. - Matthew D. Zeiler; Graham W. Taylor; Leonid Sigal; Iain A. Matthews; Rob Fergus (NIPS, 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)

3D skeletal reconstruction from low-resolution multi-view images. - Mayank Rana; Graham W. Taylor; Ian Spiro; Christoph Bregler (CVPR Workshops, 2012)

ICML2011 Unsupervised and Transfer Learning Workshop. - Daniel L. Silver; Isabelle Guyon; Graham W. Taylor; Gideon Dror; Vincent Lemaire 001 (ICML Unsupervised and Transfer Learning, 2012)

Analysis of the IJCNN 2011 UTL challenge. - Isabelle Guyon; Gideon Dror; Vincent Lemaire 001; Daniel L. Silver; Graham W. Taylor; David W. Aha (Neural Networks, 2012)

A Multi-scale Approach to Gesture Detection and Recognition. - Natalia Neverova; Christian Wolf 001; Giulio Paci; Giacomo Sommavilla; Graham W. Taylor; Florian Nebout (ICCV Workshops, 2013)

Hand Segmentation with Structured Convolutional Learning. - Natalia Neverova; Christian Wolf 001; Graham W. Taylor; Florian Nebout (ACCV (3), 2014)

Multi-task Learning of Facial Landmarks and Expression. - Terrance Devries; Kumar Biswaranjan; Graham W. Taylor (CRV, 2014)

Multi-scale Deep Learning for Gesture Detection and Localization. - Natalia Neverova; Christian Wolf 001; Graham W. Taylor; Florian Nebout (ECCV Workshops (1), 2014)

"Mental Rotation" by Optimizing Transforming Distance. - Weiguang Ding; Graham W. Taylor (CoRR, 2014)

Learning Human Pose Estimation Features with Convolutional Networks. - Arjun Jain; Jonathan Tompson; Mykhaylo Andriluka; Graham W. Taylor; Christoph Bregler (ICLR (Poster), 2014)

Neural Network Regularization via Robust Weight Factorization. - Jan Rudy; Weiguang Ding; Daniel Jiwoong Im; Graham W. Taylor (CoRR, 2014)

Human body part estimation from depth images via spatially-constrained deep learning. - Mingyuan Jiu; Christian Wolf 001; Graham W. Taylor; Atilla Baskurt (Pattern Recognit. Lett., 2014)

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 (CRV, 2015)

Deep Learning Architectures for Soil Property Prediction. - Matthew Veres; Griffin Lacey; Graham W. Taylor (CRV, 2015)

An Empirical Investigation of Minimum Probability Flow Learning Under Different Connectivity Patterns. - Daniel Jiwoong Im; Ethan Buchman; Graham W. Taylor (ECML/PKDD (1), 2015)

Scoring and Classifying with Gated Auto-Encoders. - Daniel Jiwoong Im; Graham W. Taylor (ECML/PKDD (1), 2015)

Theano-based Large-Scale Visual Recognition with Multiple GPUs. - Weiguang Ding; Ruoyan Wang; Fei Mao; Graham W. Taylor (ICLR (Workshop), 2015)

Understanding Minimum Probability Flow for RBMs Under Various Kinds of Dynamics. - Daniel Jiwoong Im; Ethan Buchman; Graham W. Taylor (ICLR (Workshop), 2015)

Hand Pose Estimation through Weakly-Supervised Learning of a Rich Intermediate Representation. - Natalia Neverova; Christian Wolf 001; Florian Nebout; Graham W. Taylor (CoRR, 2015)

Learning with hidden variables. - Yasser Roudi; Graham W. Taylor (CoRR, 2015)

Generative Class-conditional Autoencoders. - Jan Rudy; Graham W. Taylor (ICLR (Workshop), 2015)

Semisupervised Hyperspectral Image Classification via Neighborhood Graph Learning. - Daniel Jiwoong Im; Graham W. Taylor (IEEE Geosci. Remote. Sens. Lett., 2015)

Theano-MPI: A Theano-Based Distributed Training Framework. - He Ma; Fei Mao; Graham W. Taylor (Euro-Par Workshops, 2016)

Caffeinated FPGAs: FPGA framework For Convolutional Neural Networks. - Roberto DiCecco; Griffin Lacey; Jasmina Vasiljevic; Paul Chow; Graham W. Taylor; Shawki Areibi (FPT, 2016)

Learning a metric for class-conditional KNN. - Daniel Jiwoong Im; Graham W. Taylor (IJCNN, 2016)

Learning Human Identity From Motion Patterns. - Natalia Neverova; Christian Wolf 001; Griffin Lacey; Lex Fridman 001; Deepak Chandra; Brandon Barbello; Graham W. Taylor (IEEE Access, 2016)

Automatic moth detection from trap images for pest management. - Weiguang Ding; Graham W. Taylor (Comput. Electron. Agric., 2016)

Generative Adversarial Parallelization. - Daniel Jiwoong Im; He Ma; Chris Dongjoo Kim; Graham W. Taylor (CoRR, 2016)

Deep Learning on FPGAs: Past, Present, and Future. - Griffin Lacey; Graham W. Taylor; Shawki Areibi (CoRR, 2016)

ModDrop: Adaptive Multi-Modal Gesture Recognition. - Natalia Neverova; Christian Wolf 001; Graham W. Taylor; Florian Nebout (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment. - Angus Galloway; Graham W. Taylor; Aaron Ramsay; Medhat Moussa (CRV, 2017)

Explaining the Unexplained: A CLass-Enhanced Attentive Response (CLEAR) Approach to Understanding Deep Neural Networks. - Devinder Kumar; Alexander Wong; Graham W. Taylor (CVPR Workshops, 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 (ESANN, 2017)

Modout: Learning Multi-Modal Architectures by Stochastic Regularization. - Fan Li 005; Natalia Neverova; Christian Wolf 001; Graham W. Taylor (FG, 2017)

Dataset Augmentation in Feature Space. - Terrance DeVries; Graham W. Taylor (ICLR (Workshop), 2017)

An Integrated Simulator and Dataset that Combines Grasping and Vision for Deep Learning. - Matthew Veres; Medhat A. Moussa; Graham W. Taylor (CoRR, 2017)

Improved Regularization of Convolutional Neural Networks with Cutout. - Terrance Devries; Graham W. Taylor (CoRR, 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)

Hand pose estimation through semi-supervised and weakly-supervised learning. - Natalia Neverova; Christian Wolf 001; Florian Nebout; Graham W. Taylor (Comput. Vis. Image Underst., 2017)

Modeling Grasp Motor Imagery Through Deep Conditional Generative Models. - Matthew Veres; Medhat Moussa; Graham W. Taylor (IEEE Robotics Autom. Lett., 2017)

Deep Multimodal Learning: A Survey on Recent Advances and Trends. - Dhanesh Ramachandram; Graham W. Taylor (IEEE Signal Process. Mag., 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)

Self-Paced Learning with Adaptive Deep Visual Embeddings. - Vithursan Thangarasa; Graham W. Taylor (BMVC, 2018)

Real-Time End-to-End Action Detection with Two-Stream Networks. - Alaaeldin El-Nouby; Graham W. Taylor (CRV, 2018)

Generalized Hadamard-Product Fusion Operators for Visual Question Answering. - Brendan Duke; Graham W. Taylor (CRV, 2018)

Convolutional Neural Networks Regularized by Correlated Noise. - Shamak Dutta; Bryan P. Tripp; Graham W. Taylor (CRV, 2018)

Deep Learning Object Detection Methods for Ecological Camera Trap Data. - Stefan Schneider 009; Graham W. Taylor; Stefan C. Kremer (CRV, 2018)

Glimpse Clouds: Human Activity Recognition From Unstructured Feature Points. - Fabien Baradel; Christian Wolf 001; Julien Mille; Graham W. Taylor (CVPR, 2018)

Attacking Binarized Neural Networks. - Angus Galloway; Graham W. Taylor; Medhat Moussa (ICLR (Poster), 2018)

Quantitatively Evaluating GANs With Divergences Proposed for Training. - Daniel Jiwoong Im; He Ma; Graham W. Taylor; Kristin Branson (ICLR (Poster), 2018)

Understanding anatomy classification through attentive response maps. - Devinder Kumar; Vlado Menkovski; Graham W. Taylor; Alexander Wong (ISBI, 2018)

Distributed Sensor Network for Indirect Occupancy Measurement in Smart Buildings. - Colin Brennan; Graham W. Taylor; Petros Spachos (IWCMC, 2018)

BLE Beacon Based Patient Tracking in Smart Care Facilities. - Brad Kennedy; Graham W. Taylor; Petros Spachos (PerCom Workshops, 2018)

Stochastic Layer-Wise Precision in Deep Neural Networks. - Griffin Lacey; Graham W. Taylor; Shawki Areibi (UAI, 2018)

Predicting Adversarial Examples with High Confidence. - Angus Galloway; Graham W. Taylor; Medhat Moussa (CoRR, 2018)

Learning Confidence for Out-of-Distribution Detection in Neural Networks. - Terrance DeVries; Graham W. Taylor (CoRR, 2018)

Adversarial Training Versus Weight Decay. - Angus Galloway; Thomas Tanay; Graham W. Taylor (CoRR, 2018)

Leveraging Uncertainty Estimates for Predicting Segmentation Quality. - Terrance DeVries; Graham W. Taylor (CoRR, 2018)

Past, Present, and Future Approaches Using Computer Vision for Animal Re-Identification from Camera Trap Data. - Stefan Schneider 009; Graham W. Taylor; Stefan S. Linquist; Stefan C. Kremer (CoRR, 2018)

Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules. - Boris Knyazev 001; Xiao Lin; Mohamed R. Amer; Graham W. Taylor (CoRR, 2018)

Keep Drawing It: Iterative language-based image generation and editing. - Alaaeldin El-Nouby; Shikhar Sharma 001; Hannes Schulz; R. Devon Hjelm; Layla El Asri; Samira Ebrahimi Kahou; Yoshua Bengio; Graham W. Taylor (CoRR, 2018)

Adversarial Examples as an Input-Fault Tolerance Problem. - Angus Galloway; Anna Golubeva; Graham W. Taylor (CoRR, 2018)

Designing learned CO2-based occupancy estimation in smart buildings. - Colin Brennan; Graham W. Taylor; Petros Spachos (IET Wirel. Sens. Syst., 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)

Image Classification with Hierarchical Multigraph Networks. - Boris Knyazev 001; Xiao Lin; Mohamed R. Amer; Graham W. Taylor (BMVC, 2019)

Apparent Age Estimation with Relational Networks. - Eu Wern Teh; Graham W. Taylor (CRV, 2019)

Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning. - Devinder Kumar; Ibrahim Ben Daya; Kanav Vats; Jeffery Feng; Graham W. Taylor; Alexander Wong (CVPR Workshops, 2019)

Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction. - Alaaeldin El-Nouby; Shikhar Sharma 001; Hannes Schulz; R. Devon Hjelm; Layla El Asri; Samira Ebrahimi Kahou; Yoshua Bengio; Graham W. Taylor (ICCV, 2019)

Understanding Attention and Generalization in Graph Neural Networks. - Boris Knyazev 001; Graham W. Taylor; Mohamed R. Amer (NeurIPS, 2019)

Classification and Re-Identification of Fruit Fly Individuals Across Days With Convolutional Neural Networks. - Nihal Murali; Jon Schneider; Joel Levine; Graham W. Taylor (WACV, 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)

Discovery Radiomics With CLEAR-DR: Interpretable Computer Aided Diagnosis of Diabetic Retinopathy. - Devinder Kumar; Graham W. Taylor; Alexander Wong (IEEE Access, 2019)

Batch Normalization is a Cause of Adversarial Vulnerability. - Angus Galloway; Anna Golubeva; Thomas Tanay; Medhat Moussa; Graham W. Taylor (CoRR, 2019)

Understanding attention in graph neural networks. - Boris Knyazev 001; Graham W. Taylor; Mohamed R. Amer (CoRR, 2019)

On the Evaluation of Conditional GANs. - Terrance DeVries; Adriana Romero; Luis Pineda; Graham W. Taylor; Michal Drozdzal (CoRR, 2019)

Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions. - Boris Knyazev 001; Carolyn Augusta; Graham W. Taylor (CoRR, 2019)

A Nonparametric Bayesian Model for Sparse Temporal Multigraphs. - Elahe Ghalebi; Hamidreza Mahyar; Radu Grosu; Graham W. Taylor; Sinead A. Williamson (CoRR, 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)

Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. - Boris Knyazev 001; Harm de Vries; Catalina Cangea; Graham W. Taylor; Aaron C. Courville; Eugene Belilovsky (BMVC, 2020)

Response Time Analysis for Explainability of Visual Processing in CNNs. - J. Eric Taylor; Shashank Shekhar 005; Graham W. Taylor (CVPR Workshops, 2020)

Learning Permutation Invariant Representations Using Memory Networks. - Shivam Kalra; Mohammed Adnan; Graham W. Taylor; Hamid R. Tizhoosh (ECCV (29), 2020)

ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis. - Eu Wern Teh; Terrance DeVries; Graham W. Taylor (ECCV (24), 2020)

Modular Length Control for Sentence Generation. - Katya Kudashkina; Peter Wittek; Jamie Kiros; Graham W. Taylor (ESANN, 2020)

Enabling Continual Learning with Differentiable Hebbian Plasticity. - Vithursan Thangarasa; Thomas Miconi; Graham W. Taylor (IJCNN, 2020)

Learning with Less Data Via Weakly Labeled Patch Classification in Digital Pathology. - Eu Wern Teh; Graham W. Taylor (ISBI, 2020)

Instance Selection for GANs. - Terrance DeVries; Michal Drozdzal; Graham W. Taylor (NeurIPS, 2020)

Similarity Learning Networks for Animal Individual Re-Identification - Beyond the Capabilities of a Human Observer. - Stefan Schneider 009; Graham W. Taylor; Stefan C. Kremer (WACV Workshops, 2020)

Sample-Efficient Model-based Actor-Critic for an Interactive Dialogue Task. - Katya Kudashkina; Valliappa Chockalingam; Graham W. Taylor; Michael Bowling (CoRR, 2020)

Generative Graph Perturbations for Scene Graph Prediction. - Boris Knyazev 001; Harm de Vries; Catalina Cangea; Graham W. Taylor; Aaron C. Courville; Eugene Belilovsky (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)

Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization. - Michal Lisicki; Arash Afkanpour; Graham W. Taylor (CoRR, 2020)

Building LEGO Using Deep Generative Models of Graphs. - Rylee Thompson; Elahe Ghalebi; Terrance DeVries; Graham W. Taylor (CoRR, 2020)

Multisource Domain Adaptation for Remote Sensing Using Deep Neural Networks. - Ahmed Elshamli; Graham W. Taylor; Shawki Areibi (IEEE Trans. Geosci. Remote. Sens., 2020)

SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation. - Brendan Duke; Abdalla Ahmed; Christian Wolf 001; Parham Aarabi; Graham W. Taylor (CVPR, 2021)

LOHO: Latent Optimization of Hairstyles via Orthogonalization. - Rohit Saha; Brendan Duke; Florian Shkurti; Graham W. Taylor; Parham Aarabi (CVPR, 2021)

Unconstrained Scene Generation with Locally Conditioned Radiance Fields. - Terrance DeVries; Miguel Ángel Bautista 001; Nitish Srivastava; Graham W. Taylor; Joshua M. Susskind (ICCV, 2021)

Generative Compositional Augmentations for Scene Graph Prediction. - Boris Knyazev 001; Harm de Vries; Catalina Cangea; Graham W. Taylor; Aaron C. Courville; Eugene Belilovsky (ICCV, 2021)

Context-aware Scene Graph Generation with Seq2Seq Transformers. - Yichao Lu; Himanshu Rai; Jason Chang; Boris Knyazev 001; Guangwei Yu; Shashank Shekhar 005; Graham W. Taylor; Maksims Volkovs (ICCV, 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; et al. (ISTAS, 2021)

One Health Informatics and the stewardship of complex systems. - Graham W. Taylor; Theresa Bernardo; Deborah A. Stacey; Kassy Raymond; Rozita Dara 001; Samira Yousefinaghani; Ethan Pike (ISTAS, 2021)

Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning. - Hyunsoo Chung; Jungtaek Kim 001; Boris Knyazev 001; Jinhwi Lee; Graham W. Taylor; Jaesik Park; Minsu Cho (NeurIPS, 2021)

Parameter Prediction for Unseen Deep Architectures. - Boris Knyazev 001; Michal Drozdzal; Graham W. Taylor; Adriana Romero-Soriano (NeurIPS, 2021)

An Empirical Study of Neural Kernel Bandits. - Michal Lisicki; Arash Afkanpour; Graham W. Taylor (CoRR, 2021)

Domain-Agnostic Clustering with Self-Distillation. - Mohammed Adnan; Yani A. Ioannou; Chuan-Yung Tsai; Graham W. Taylor (CoRR, 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)

DelphAI: A human-centered approach to time-series forecasting. - Kristina L. Kupferschmidt; Joshua August Gus Skorburg; Graham W. Taylor (IEEE Big Data, 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 (CRV, 2022)

Understanding the impact of image and input resolution on deep digital pathology patch classifiers. - Eu Wern Teh; Graham W. Taylor (CRV, 2022)

On Evaluation Metrics for Graph Generative Models. - Rylee Thompson; Boris Knyazev 001; Elahe Ghalebi; Jungtaek Kim 001; Graham W. Taylor (ICLR, 2022)

Learning with Less Labels in Digital Pathology Via Scribble Supervision from Natural Images. - Eu Wern The; Graham W. Taylor (ISBI, 2022)

Learning with Less Labels in Digital Pathology via Scribble Supervision from Natural Images. - Eu Wern Teh; Graham W. Taylor (CoRR, 2022)

DeepRNG: Towards Deep Reinforcement Learning-Assisted Generative Testing of Software. - Chuan-Yung Tsai; Graham W. Taylor (CoRR, 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)

Sparsifiner: Learning Sparse Instance-Dependent Attention for Efficient Vision Transformers. - Cong Wei 001; Brendan Duke; Ruowei Jiang; Parham Aarabi; Graham W. Taylor; Florian Shkurti (CVPR, 2023)

Which Tokens to Use? Investigating Token Reduction in Vision Transformers. - Joakim Bruslund Haurum; Sergio Escalera; Graham W. Taylor; Thomas B. Moeslund (ICCV (Workshops), 2023)

The Catalog Problem: Clustering and Ordering Variable-Sized Sets. - Mateusz Maria Jurewicz; Graham W. Taylor; Leon Derczynski (ICML, 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; et al. (NeurIPS, 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)

Empirically Validating Conformal Prediction on Modern Vision Architectures Under Distribution Shift and Long-tailed Data. - Kevin Kasa; Graham W. Taylor (CoRR, 2023)

Bandit-Driven Batch Selection for Robust Learning under Label Noise. - Michal Lisicki; Mihai Nica; 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)

Stable Rivers: A Case Study in the Application of Text-to-Image Generative Models for Earth Sciences. - Cody Kupferschmidt; A. D. Binns; Kristina L. Kupferschmidt; Graham W. Taylor (CoRR, 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)

Open-Vocabulary Temporal Action Localization using Multimodal Guidance. - Akshita Gupta; Aditya Arora; Sanath Narayan; Salman Khan 001; Fahad Shahbaz Khan; Graham W. Taylor (BMVC, 2024)

Agglomerative Token Clustering. - Joakim Bruslund Haurum; Sergio Escalera; Graham W. Taylor; Thomas B. Moeslund (ECCV (57), 2024)

BIOSCAN-5M: A Multimodal Dataset for Insect Biodiversity. - 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; et al. (NeurIPS, 2024)

BIOSCAN-CLIP: Bridging Vision and Genomics for Biodiversity Monitoring at Scale. - ZeMing Gong; Austin T. Wang; Joakim Bruslund Haurum; Scott C. Lowe; Graham W. Taylor; Angel X. Chang (CoRR, 2024)

Adapting Conformal Prediction to Distribution Shifts Without Labels. - Kevin Kasa; Zhiyu Zhang; Heng Yang; Graham W. Taylor (CoRR, 2024)

An Empirical Study into Clustering of Unseen Datasets with Self-Supervised Encoders. - Scott C. Lowe; Joakim Bruslund Haurum; Sageev Oore; Thomas B. Moeslund; Graham W. Taylor (CoRR, 2024)

Food for thought: How can machine learning help better predict and understand changes in food prices? - Kristina L. Kupferschmidt; James Requiema; Mya Simpson; Zohrah Varsallay; Ethan Jackson; Cody Kupferschmidt; Sara El-Shawa; Graham W. Taylor (CoRR, 2024)

BarcodeMamba: State Space Models for Biodiversity Analysis. - Tiancheng Gao; Graham W. Taylor (CoRR, 2024)

GCNet: Probing self-similarity learning for Generalized Counting Network. - Mingjie Wang 002; Yande Li; Jun Zhou; Graham W. Taylor; Minglun Gong (Pattern Recognit., 2024)

Bridging the AI Gap: Evaluating the Impact of an AI Education Program for Caregivers on Parental Leave. - Kristina L. Kupferschmidt; Flora Wan; Juan Carrasquilla Alvarez; Dora Gaviria Castaño; Graham W. Taylor; Sedef Akinli Kocak (AAAI, 2025)

Taxonomic Reasoning for Rare Arthropods: Combining Dense Image Captioning and RAG for Interpretable Classification. - Nathaniel Lesperance; Sujeevan Ratnasingham; Graham W. Taylor (Canadian AI, 2025)

CLIBD: Bridging Vision and Genomics for Biodiversity Monitoring at Scale. - ZeMing Gong; Austin T. Wang; Xiaoliang Huo; Joakim Bruslund Haurum; Scott C. Lowe; Graham W. Taylor; Angel X. Chang (ICLR, 2025)

Adapting Prediction Sets to Distribution Shifts Without Labels. - Kevin Kasa; Zhiyu Zhang; Heng Yang; Graham W. Taylor (UAI, 2025)

LoSA: Long-Short-Range Adapter for Scaling End-to-End Temporal Action Localization. - Akshita Gupta; Gaurav Mittal; Ahmed Magooda; Ye Yu 003; Graham W. Taylor; Mei Chen (WACV, 2025)

Neuron-based explanations of neural networks sacrifice completeness and interpretability. - Nolan Simran Dey; J. Eric Taylor; Alexander Wong; Bryan P. Tripp; Graham W. Taylor (Trans. Mach. Learn. Res., 2025)

Enhancing DNA Foundation Models to Address Masking Inefficiencies. - Monireh Safari; Pablo Millan Arias; Scott C. Lowe; Lila Kari; Angel X. Chang; Graham W. Taylor (CoRR, 2025)

A multi-modal dataset for insect biodiversity with imagery and DNA at the trap and individual level. - Johanna Orsholm; John Quinto; Hannu Autto; Gaia Banelyte; Nicolas Chazot; Jeremy deWaard; Stephanie deWaard; Arielle Farrell; Brendan Furneaux; Bess Hardwick; Nao Ito; Amlan Kar; et al. (CoRR, 2025)