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Disentangling Transfer and Interference in Multi-Domain Learning


Jul 16, 2021
Yipeng Zhang, Tyler L. Hayes, Christopher Kanan


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Replay in Deep Learning: Current Approaches and Missing Biological Elements


Apr 01, 2021
Tyler L. Hayes, Giri P. Krishnan, Maxim Bazhenov, Hava T. Siegelmann, Terrence J. Sejnowski, Christopher Kanan


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Avalanche: an End-to-End Library for Continual Learning


Apr 01, 2021
Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido van de Ven, Martin Mundt, Qi She, Keiland Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German I. Parisi, Fabio Cuzzolin, Andreas Tolias, Simone Scardapane, Luca Antiga, Subutai Amhad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni

* Official Website: https://avalanche.continualai.org 

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Self-Supervised Training Enhances Online Continual Learning


Mar 25, 2021
Jhair Gallardo, Tyler L. Hayes, Christopher Kanan


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Selective Replay Enhances Learning in Online Continual Analogical Reasoning


Mar 06, 2021
Tyler L. Hayes, Christopher Kanan


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Improved Robustness to Open Set Inputs via Tempered Mixup


Sep 10, 2020
Ryne Roady, Tyler L. Hayes, Christopher Kanan

* Proceedings of the ECCV 2020 Workshop on Adversarial Robustness in the Real World 

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RODEO: Replay for Online Object Detection


Aug 14, 2020
Manoj Acharya, Tyler L. Hayes, Christopher Kanan

* Accepted for poster presentation at BMVC2020 

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Do We Need Fully Connected Output Layers in Convolutional Networks?


Apr 29, 2020
Zhongchao Qian, Tyler L. Hayes, Kushal Kafle, Christopher Kanan


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Are Out-of-Distribution Detection Methods Effective on Large-Scale Datasets?


Oct 30, 2019
Ryne Roady, Tyler L. Hayes, Ronald Kemker, Ayesha Gonzales, Christopher Kanan


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REMIND Your Neural Network to Prevent Catastrophic Forgetting


Oct 06, 2019
Tyler L. Hayes, Kushal Kafle, Robik Shrestha, Manoj Acharya, Christopher Kanan


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Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis


Sep 04, 2019
Tyler L. Hayes, Christopher Kanan


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Memory Efficient Experience Replay for Streaming Learning


Sep 16, 2018
Tyler L. Hayes, Nathan D. Cahill, Christopher Kanan


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Compassionately Conservative Balanced Cuts for Image Segmentation


Mar 27, 2018
Nathan D. Cahill, Tyler L. Hayes, Renee T. Meinhold, John F. Hamilton

* Long version of paper accepted at CVPR 2018 

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Efficiently Computing Piecewise Flat Embeddings for Data Clustering and Image Segmentation


Dec 20, 2016
Renee T. Meinhold, Tyler L. Hayes, Nathan D. Cahill

* Presented at the 2016 IEEE MIT Undergraduate Research Technology Conference (http://ieee.scripts.mit.edu/conference/index.php

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