Taylor, Graham W.

68 publications

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

AAAI 2025 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

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

ICLRW 2025 Enhancing DNA Foundation Models to Address Masking Inefficiencies Monireh Safari, Pablo Andres Millan Arias, Scott C. Lowe, Lila Kari, Angel X Chang, Graham W. Taylor

ICML 2025 LAST SToP for Modeling Asynchronous Time Series Shubham Gupta, Thibaut Durand, Graham W. Taylor, Lilian Bialokozowicz

TMLR 2025 Neuron-Based Explanations of Neural Networks Sacrifice Completeness and Interpretability Nolan Simran Dey, Eric Taylor, Alexander Wong, Bryan P. Tripp, Graham W. Taylor

ECCV 2024 Agglomerative Token Clustering Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor, Thomas B. Moeslund

ICMLW 2024 An Empirical Study into Clustering of Unseen Datasets with Self-Supervised Foundation Models Scott C. Lowe, Joakim Bruslund Haurum, Sageev Oore, Thomas B. Moeslund, Graham W. Taylor

NeurIPS 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 Fieguth, Angel X. Chang

NeurIPSW 2024 BarcodeMamba: State Space Models for Biodiversity Analysis Tiancheng Gao, Graham W. Taylor

NeurIPS 2023 A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset Zahra Gharaee, ZeMing Gong, Nicholas Pellegrino, Iuliia Zarubiieva, Joakim Bruslund Haurum, Scott Lowe, Jaclyn McKeown, Chris Ho, Joschka McLeod, Yi-Yun Wei, Jireh Agda, Sujeevan Ratnasingham, Dirk Steinke, Angel Chang, Graham W. Taylor, Paul Fieguth

NeurIPSW 2023 Bandit-Driven Batch Selection for Robust Learning Under Label Noise Michal Lisicki, Mihai Nica, Graham W. Taylor

NeurIPSW 2023 Bandit-Driven Batch Selection for Robust Learning Under Label Noise Michal Lisicki, Graham W. Taylor, Mihai Nica

TMLR 2023 Bounding Generalization Error with Input Compression: An Empirical Study with Infinite-Width Networks Angus Galloway, Anna Golubeva, Mahmoud Salem, Mihai Nica, Yani Ioannou, Graham W. Taylor

ICMLW 2023 Empirically Validating Conformal Prediction on Modern Vision Architectures Under Distribution Shift and Long-Tailed Data Kevin Kasa, Graham W. Taylor

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

ICML 2023 The Catalog Problem: Clustering and Ordering Variable-Sized Sets Mateusz Maria Jurewicz, Graham W. Taylor, Leon Derczynski

ICCVW 2023 Which Tokens to Use? Investigating Token Reduction in Vision Transformers Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor, Thomas B. Moeslund

NeurIPSW 2023 Zero-Shot Clustering of Embeddings with Pretrained and Self-Supervised Learnt Encoders Scott C Lowe, Joakim Bruslund Haurum, Sageev Oore, Thomas B. Moeslund, Graham W. Taylor

NeurIPS 2022 FlyView: A Bio-Informed Optical Flow Truth Dataset for Visual Navigation Using Panoramic Stereo Vision Alix Leroy, Graham W. Taylor

ICMLW 2022 Monitoring Shortcut Learning Using Mutual Information Mohammed Adnan, Yani Ioannou, Kenyon Tsai, Angus Galloway, Hamid Tizhoosh, Graham W. Taylor

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

NeurIPS 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

ICCV 2021 Context-Aware Scene Graph Generation with Seq2Seq Transformers Yichao Lu, Himanshu Rai, Jason Chang, Boris Knyazev, Guangwei Yu, Shashank Shekhar, Graham W. Taylor, Maksims Volkovs

ICCV 2021 Generative Compositional Augmentations for Scene Graph Prediction Boris Knyazev, Harm de Vries, Cătălina Cangea, Graham W. Taylor, Aaron Courville, Eugene Belilovsky

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

NeurIPSW 2021 Neural Structure Mapping for Learning Abstract Visual Analogies Shashank Shekhar, Graham W. Taylor

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

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

ICCV 2021 Unconstrained Scene Generation with Locally Conditioned Radiance Fields Terrance DeVries, Miguel Angel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind

NeurIPSW 2020 Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization Michal Lisicki, Arash Afkanpour, Graham W Taylor

NeurIPSW 2020 Identifying and Interpreting Tuning Dimensions in Deep Networks Nolan Simran Dey, Eric Taylor, Bryan P. Tripp, Alexander Wong, Graham W Taylor

NeurIPS 2020 Instance Selection for GANs Terrance DeVries, Michal Drozdzal, Graham W. Taylor

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

CVPRW 2020 Response Time Analysis for Explainability of Visual Processing in CNNs J. Eric Taylor, Shashank Shekhar, Graham W. Taylor

ICMLW 2019 Batch Normalization Is a Cause of Adversarial Vulnerability Angus Galloway, Anna Golubeva, Thomas Tanay, Medhat Moussa, Graham W. Taylor

CVPRW 2019 Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning Devinder Kumar, Ibrahim Ben Daya, Kanav Vats, Jeffery Feng, Graham W. Taylor, Alexander Wong

WACV 2019 Classification and Re-Identification of Fruit Fly Individuals Across Days with Convolutional Neural Networks Nihal Murali, Jon Schneider, Joel Levine, Graham W. Taylor

ICMLW 2019 Differentiable Hebbian Plasticity for Continual Learning Vithursan Thangarasa, Thomas Miconi, Graham W. Taylor

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

NeurIPS 2019 Understanding Attention and Generalization in Graph Neural Networks Boris Knyazev, Graham W. Taylor, Mohamed Amer

ICLR 2018 Attacking Binarized Neural Networks Angus Galloway, Graham W. Taylor, Medhat Moussa

CVPR 2018 Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points Fabien Baradel, Christian Wolf, Julien Mille, Graham W. Taylor

ICLR 2018 Quantitatively Evaluating GANs with Divergences Proposed for Training Daniel Jiwoong Im, He Ma, Graham W. Taylor, Kristin Branson

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

ICLR 2017 Dataset Augmentation in Feature Space Terrance DeVries, Graham W. Taylor

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

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

ICLR 2015 Generative Class-Conditional Autoencoders Jan Rudy, Graham W. Taylor

ECML-PKDD 2015 Scoring and Classifying with Gated Auto-Encoders Daniel Jiwoong Im, Graham W. Taylor

ICLR 2015 Theano-Based Large-Scale Visual Recognition with Multiple GPUs Weiguang Ding, Ruoyan Wang, Fei Mao, Graham W. Taylor

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

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

ECCVW 2014 Multi-Scale Deep Learning for Gesture Detection and Localization Natalia Neverova, Christian Wolf, Graham W. Taylor, Florian Nebout

ICCVW 2013 A Multi-Scale Approach to Gesture Detection and Recognition Natalia Neverova, Christian Wolf, Giulio Paci, Giacomo Sommavilla, Graham W. Taylor, Florian Nebout

CVPRW 2012 3D Skeletal Reconstruction from Low-Resolution Multi-View Images Mayank Rana, Graham W. Taylor, Ian Spiro, Christoph Bregler

ICCV 2011 Adaptive Deconvolutional Networks for Mid and High Level Feature Learning Matthew D. Zeiler, Graham W. Taylor, Rob Fergus

NeurIPS 2011 Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines Matthew D. Zeiler, Graham W. Taylor, Leonid Sigal, Iain Matthews, Rob Fergus

CVPR 2011 Learning Invariance Through Imitation Graham W. Taylor, Ian Spiro, Christoph Bregler, Rob Fergus

JMLR 2011 Two Distributed-State Models for Generating High-Dimensional Time Series Graham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis

ECCV 2010 Convolutional Learning of Spatio-Temporal Features Graham W. Taylor, Rob Fergus, Yann LeCun, Christoph Bregler

CVPR 2010 Deconvolutional Networks Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylor, Robert Fergus

CVPR 2010 Dynamical Binary Latent Variable Models for 3D Human Pose Tracking Graham W. Taylor, Leonid Sigal, David J. Fleet, Geoffrey E. Hinton

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

ICML 2009 Factored Conditional Restricted Boltzmann Machines for Modeling Motion Style Graham W. Taylor, Geoffrey E. Hinton

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

NeurIPS 2008 The Recurrent Temporal Restricted Boltzmann Machine Ilya Sutskever, Geoffrey E. Hinton, Graham W. Taylor

NeurIPS 2006 Modeling Human Motion Using Binary Latent Variables Graham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis