Tyler L. Hayes

According to our database, Tyler L. Hayes authored at least 30 papers between 2016 and 2024.

Collaborative distances:

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

2024

Continual Learning: Applications and the Road Forward.

Eli Verwimp, Rahaf Aljundi, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, Eyke Hüllermeier, Christopher Kanan, Dhireesha Kudithipudi, Christoph H. Lampert, Martin Mundt, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven

Trans. Mach. Learn. Res., 2024

What could go wrong? Discovering and describing failure modes in computer vision.

Gabriela Csurka, Tyler L. Hayes, Diane Larlus, Riccardo Volpi

CoRR, 2024

PANDAS: Prototype-based Novel Class Discovery and Detection.

Tyler L. Hayes, César R. de Souza, Namil Kim, Jiwon Kim, Riccardo Volpi, Diane Larlus

CoRR, 2024

SHiNe: Semantic Hierarchy Nexus for Open-Vocabulary Object Detection.

Mingxuan Liu, Tyler L. Hayes, Elisa Ricci, Gabriela Csurka, Riccardo Volpi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

SIESTA: Efficient Online Continual Learning with Sleep.

Md Yousuf Harun, Jhair Gallardo, Tyler L. Hayes, Ronald Kemker, Christopher Kanan

Trans. Mach. Learn. Res., 2023

How Efficient Are Today's Continual Learning Algorithms?

Md Yousuf Harun, Jhair Gallardo, Tyler L. Hayes, Christopher Kanan

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

Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program.

Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

2022

Online Continual Learning for Embedded Devices.

Tyler L. Hayes, Christopher Kanan

Proceedings of the Conference on Lifelong Learning Agents, 2022

Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2.

Zachary Alan Daniels, Aswin Raghavan, Jesse Hostetler, Abrar Rahman, Indranil Sur, Michael R. Piacentino, Ajay Divakaran, Roberto Corizzo, Kamil Faber, Nathalie Japkowicz, Michael Baron, James Seale Smith, Sahana Pramod Joshi, Zsolt Kira, Cameron Ethan Taylor, Mustafa Burak Gurbuz, Constantine Dovrolis, Tyler L. Hayes, Christopher Kanan, Jhair Gallardo

Proceedings of the Conference on Lifelong Learning Agents, 2022

Can I see an Example? Active Learning the Long Tail of Attributes and Relations.

Tyler L. Hayes, Maximilian Nickel, Christopher Kanan, Ludovic Denoyer, Arthur Szlam

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games.

Indranil Sur, Zachary Daniels, Abrar Rahman, Kamil Faber, Gianmarco J. Gallardo, Tyler L. Hayes, Cameron E. Taylor, Mustafa Burak Gurbuz, James Seale Smith, Sahana Pramod Joshi, Nathalie Japkowicz, Michael Baron, Zsolt Kira, Christopher Kanan, Roberto Corizzo, Ajay Divakaran, Michael R. Piacentino, Jesse Hostetler, Aswin Raghavan

Proceedings of the Second International Conference on AI-ML Systems, 2022

2021

Replay in Deep Learning: Current Approaches and Missing Biological Elements.

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

Neural Comput., 2021

Disentangling Transfer and Interference in Multi-Domain Learning.

Yipeng Zhang, Tyler L. Hayes, Christopher Kanan

CoRR, 2021

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

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

CoRR, 2021

Self-Supervised Training Enhances Online Continual Learning.

Jhair Gallardo, Tyler L. Hayes, Christopher Kanan

CoRR, 2021

Avalanche: An End-to-End Library for Continual Learning.

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

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

Selective Replay Enhances Learning in Online Continual Analogical Reasoning.

Tyler L. Hayes, Christopher Kanan

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

Self-Supervised Training Enhances Online Continual Learning.

Gianmarco J. Gallardo, Tyler L. Hayes, Christopher Kanan

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

Do We Need Fully Connected Output Layers in Convolutional Networks?

Zhongchao Qian, Tyler L. Hayes, Kushal Kafle, Christopher Kanan

CoRR, 2020

Improved Robustness to Open Set Inputs via Tempered Mixup.

Ryne Roady, Tyler L. Hayes, Christopher Kanan

Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

REMIND Your Neural Network to Prevent Catastrophic Forgetting.

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

Proceedings of the Computer Vision - ECCV 2020, 2020

Stream-51: Streaming Classification and Novelty Detection from Videos.

Ryne Roady, Tyler L. Hayes, Hitesh Vaidya, Christopher Kanan

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

Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis.

Tyler L. Hayes, Christopher Kanan

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

RODEO: Replay for Online Object Detection.

Manoj Acharya, Tyler L. Hayes, Christopher Kanan

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

2019

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

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

CoRR, 2019

Memory Efficient Experience Replay for Streaming Learning.

Tyler L. Hayes, Nathan D. Cahill, Christopher Kanan

Proceedings of the International Conference on Robotics and Automation, 2019

2018

New Metrics and Experimental Paradigms for Continual Learning.

Tyler L. Hayes, Ronald Kemker, Nathan D. Cahill, Christopher Kanan

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

Compassionately Conservative Balanced Cuts for Image Segmentation.

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

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

Measuring Catastrophic Forgetting in Neural Networks.

Ronald Kemker, Marc McClure, Angelina Abitino, Tyler L. Hayes, Christopher Kanan

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2016

Efficiently Computing Piecewise Flat Embeddings for Data Clustering and Image Segmentation.

Renee T. Meinhold, Tyler L. Hayes, Nathan D. Cahill

CoRR, 2016