Tyler L. Hayes
Title
Cited by
Cited by
Year
Measuring Catastrophic Forgetting in Neural Networks
R Kemker, M McClure, A Abitino, TL Hayes, C Kanan
32nd AAAI Conference on Artificial Intelligence (AAAI-18), 3390-3398, 2018
1172018
Memory Efficient Experience Replay for Streaming Learning
TL Hayes, ND Cahill, C Kanan
2019 IEEE International Conference on Robotics and Automation (ICRA-2019), 2019
222019
New metrics and experimental paradigms for continual learning
TL Hayes, R Kemker, ND Cahill, C Kanan
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
92018
Lifelong machine learning with deep streaming linear discriminant analysis
TL Hayes, C Kanan
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2020
32020
Efficiently computing piecewise flat embeddings for data clustering and image segmentation
RT Meinhold, TL Hayes, ND Cahill
2016 IEEE MIT Undergraduate Research Technology Conference (URTC), 1-4, 2016
32016
Are Out-of-Distribution Detection Methods Effective on Large-Scale Datasets?
R Roady, TL Hayes, R Kemker, A Gonzales, C Kanan
arXiv preprint arXiv:1910.14034, 2019
22019
Do We Need Fully Connected Output Layers in Convolutional Networks?
Z Qian, TL Hayes, K Kafle, C Kanan
arXiv preprint arXiv:2004.13587, 2020
2020
REMIND Your Neural Network to Prevent Catastrophic Forgetting
TL Hayes, K Kafle, R Shrestha, M Acharya, C Kanan
arXiv preprint arXiv:1910.02509, 2019
2019
Compassionately conservative balanced cuts for image segmentation
ND Cahill, TL Hayes, RT Meinhold, JF Hamilton
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
2018
Piecewise flat embeddings for hyperspectral image analysis
TL Hayes, RT Meinhold, JF Hamilton Jr, ND Cahill
Algorithms and Technologies for Multispectral, Hyperspectral, and …, 2017
2017
Compassionately Conservative Normalized Cuts for Image Segmentation
TL Hayes
RIT Master's Thesis, 2017
2017
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Articles 1–11