Tyler L. Hayes

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 43

Top Topics

Efficiently Computing

Reinforcement Learning

Novelty Detection

Top Venues

Publications

Mingxuan Liu, Tyler L. Hayes, Elisa Ricci, Gabriela Csurka, Riccardo Volpi
SHiNe: Semantic Hierarchy Nexus for Open-vocabulary Object Detection. CoRR (2024)
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
Continual Learning: Applications and the Road Forward. Trans. Mach. Learn. Res. 2024 (2024)
Tyler L. Hayes, César R. de Souza, Namil Kim, Jiwon Kim, Riccardo Volpi, Diane Larlus
PANDAS: Prototype-based Novel Class Discovery and Detection. CoRR (2024)
Eli Verwimp, 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
Continual Learning: Applications and the Road Forward. CoRR (2023)
Md Yousuf Harun, Jhair Gallardo, Tyler L. Hayes, Christopher Kanan
How Efficient Are Today's Continual Learning Algorithms? CoRR (2023)
Md Yousuf Harun, Jhair Gallardo, Tyler L. Hayes, Ronald Kemker, Christopher Kanan
SIESTA: Efficient Online Continual Learning with Sleep. CoRR (2023)
Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes
Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program. AAAI Bridge Program (2023)
Md Yousuf Harun, Jhair Gallardo, Tyler L. Hayes, Christopher Kanan
How Efficient Are Today's Continual Learning Algorithms? CVPR Workshops (2023)
Md Yousuf Harun, Jhair Gallardo, Tyler L. Hayes, Ronald Kemker, Christopher Kanan
SIESTA: Efficient Online Continual Learning with Sleep. Trans. Mach. Learn. Res. 2023 (2023)
Tyler L. Hayes, Maximilian Nickel, Christopher Kanan, Ludovic Denoyer, Arthur Szlam
Can I see an Example? Active Learning the Long Tail of Attributes and Relations. CoRR (2022)
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 Piacentino, Jesse Hostetler, Aswin Raghavan
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games. AIMLSystems (2022)
Tyler L. Hayes, Christopher Kanan
Online Continual Learning for Embedded Devices. CoLLAs (2022)
Zachary Alan Daniels, Aswin Raghavan, Jesse Hostetler, Abrar Rahman, Indranil Sur, Michael 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
Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2. CoLLAs (2022)
Indranil Sur, Zachary Daniels, Abrar Rahman, Kamil Faber, Gianmarco J. Gallardo, Tyler L. Hayes, Cameron E. Taylor, Mustafa Burak Gurbuz, James Seale Smith, Sahana Joshi, Nathalie Japkowicz, Michael Baron, Zsolt Kira, Christopher Kanan, Roberto Corizzo, Ajay Divakaran, Michael R. Piacentino, Jesse Hostetler, Aswin Raghavan
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games. CoRR (2022)
Tyler L. Hayes, Maximillian Nickel, Christopher Kanan, Ludovic Denoyer, Arthur Szlam
Can I see an Example? Active Learning the Long Tail of Attributes and Relations. BMVC (2022)
Tyler L. Hayes, Christopher Kanan
Online Continual Learning for Embedded Devices. CoRR (2022)
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 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
Avalanche: An End-to-End Library for Continual Learning. CVPR Workshops (2021)
Gianmarco J. Gallardo, Tyler L. Hayes, Christopher Kanan
Self-Supervised Training Enhances Online Continual Learning. BMVC (2021)
Yipeng Zhang, Tyler L. Hayes, Christopher Kanan
Disentangling Transfer and Interference in Multi-Domain Learning. CoRR (2021)
Tyler L. Hayes, Christopher Kanan
Selective Replay Enhances Learning in Online Continual Analogical Reasoning. CVPR Workshops (2021)
Tyler L. Hayes, Christopher Kanan
Selective Replay Enhances Learning in Online Continual Analogical Reasoning. CoRR (2021)
Tyler L. Hayes, Giri P. Krishnan, Maxim Bazhenov, Hava T. Siegelmann, Terrence J. Sejnowski, Christopher Kanan
Replay in Deep Learning: Current Approaches and Missing Biological Elements. CoRR (2021)
Tyler L. Hayes, Giri P. Krishnan, Maxim Bazhenov, Hava T. Siegelmann, Terrence J. Sejnowski, Christopher Kanan
Replay in Deep Learning: Current Approaches and Missing Biological Elements. Neural Comput. 33 (11) (2021)
Jhair Gallardo, Tyler L. Hayes, Christopher Kanan
Self-Supervised Training Enhances Online Continual Learning. CoRR (2021)
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 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
Avalanche: an End-to-End Library for Continual Learning. CoRR (2021)
Manoj Acharya, Tyler L. Hayes, Christopher Kanan
RODEO: Replay for Online Object Detection. BMVC (2020)
Ryne Roady, Tyler L. Hayes, Christopher Kanan
Improved Robustness to Open Set Inputs via Tempered Mixup. ECCV Workshops (1) (2020)
Tyler L. Hayes, Christopher Kanan
Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis. CVPR Workshops (2020)
Ryne Roady, Tyler L. Hayes, Hitesh Vaidya, Christopher Kanan
Stream-51: Streaming Classification and Novelty Detection from Videos. CVPR Workshops (2020)
Ryne Roady, Tyler L. Hayes, Christopher Kanan
Improved Robustness to Open Set Inputs via Tempered Mixup. CoRR (2020)
Zhongchao Qian, Tyler L. Hayes, Kushal Kafle, Christopher Kanan
Do We Need Fully Connected Output Layers in Convolutional Networks? CoRR (2020)
Manoj Acharya, Tyler L. Hayes, Christopher Kanan
RODEO: Replay for Online Object Detection. CoRR (2020)
Tyler L. Hayes, Kushal Kafle, Robik Shrestha, Manoj Acharya, Christopher Kanan
REMIND Your Neural Network to Prevent Catastrophic Forgetting. ECCV (8) (2020)
Tyler L. Hayes, Nathan D. Cahill, Christopher Kanan
Memory Efficient Experience Replay for Streaming Learning. ICRA (2019)
Tyler L. Hayes, Kushal Kafle, Robik Shrestha, Manoj Acharya, Christopher Kanan
REMIND Your Neural Network to Prevent Catastrophic Forgetting. CoRR (2019)
Ryne Roady, Tyler L. Hayes, Ronald Kemker, Ayesha Gonzales, Christopher Kanan
Are Out-of-Distribution Detection Methods Effective on Large-Scale Datasets? CoRR (2019)
Tyler L. Hayes, Christopher Kanan
Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis. CoRR (2019)
Nathan D. Cahill, Tyler L. Hayes, Renee T. Meinhold, John F. Hamilton
Compassionately Conservative Balanced Cuts for Image Segmentation. CVPR (2018)
Ronald Kemker, Marc McClure, Angelina Abitino, Tyler L. Hayes, Christopher Kanan
Measuring Catastrophic Forgetting in Neural Networks. AAAI (2018)
Tyler L. Hayes, Ronald Kemker, Nathan D. Cahill, Christopher Kanan
New Metrics and Experimental Paradigms for Continual Learning. CVPR Workshops (2018)
Nathan D. Cahill, Tyler L. Hayes, Renee T. Meinhold, John F. Hamilton
Compassionately Conservative Balanced Cuts for Image Segmentation. CoRR (2018)
Tyler L. Hayes, Nathan D. Cahill, Christopher Kanan
Memory Efficient Experience Replay for Streaming Learning. CoRR (2018)
Renee T. Meinhold, Tyler L. Hayes, Nathan D. Cahill
Efficiently Computing Piecewise Flat Embeddings for Data Clustering and Image Segmentation. CoRR (2016)