Efficiently Computing Piecewise Flat Embeddings for Data Clustering and Image Segmentation. - Renee T. Meinhold; Tyler L. Hayes; Nathan D. Cahill (CoRR, 2016)

Measuring Catastrophic Forgetting in Neural Networks. - Ronald Kemker; Marc McClure; Angelina Abitino; Tyler L. Hayes; Christopher Kanan (AAAI, 2018)

Compassionately Conservative Balanced Cuts for Image Segmentation. - Nathan D. Cahill; Tyler L. Hayes; Renee T. Meinhold; John F. Hamilton (CVPR, 2018)

New Metrics and Experimental Paradigms for Continual Learning. - Tyler L. Hayes; Ronald Kemker; Nathan D. Cahill; Christopher Kanan (CVPR Workshops, 2018)

Memory Efficient Experience Replay for Streaming Learning. - Tyler L. Hayes; Nathan D. Cahill; Christopher Kanan (ICRA, 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)

RODEO: Replay for Online Object Detection. - Manoj Acharya; Tyler L. Hayes; Christopher Kanan (BMVC, 2020)

Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis. - Tyler L. Hayes; Christopher Kanan (CVPR Workshops, 2020)

Stream-51: Streaming Classification and Novelty Detection from Videos. - Ryne Roady; Tyler L. Hayes; Hitesh Vaidya; Christopher Kanan (CVPR Workshops, 2020)

REMIND Your Neural Network to Prevent Catastrophic Forgetting. - Tyler L. Hayes; Kushal Kafle; Robik Shrestha; Manoj Acharya; Christopher Kanan (ECCV (8), 2020)

Improved Robustness to Open Set Inputs via Tempered Mixup. - Ryne Roady; Tyler L. Hayes; Christopher Kanan (ECCV Workshops (1), 2020)

Do We Need Fully Connected Output Layers in Convolutional Networks? - Zhongchao Qian; Tyler L. Hayes; Kushal Kafle; Christopher Kanan (CoRR, 2020)

Self-Supervised Training Enhances Online Continual Learning. - Gianmarco J. Gallardo; Tyler L. Hayes; Christopher Kanan (BMVC, 2021)

Selective Replay Enhances Learning in Online Continual Analogical Reasoning. - Tyler L. Hayes; Christopher Kanan (CVPR Workshops, 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; et al. (CVPR Workshops, 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; et al. (CoRR, 2021)

Disentangling Transfer and Interference in Multi-Domain Learning. - Yipeng Zhang; Tyler L. Hayes; Christopher Kanan (CoRR, 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)

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; et al. (AIMLSystems, 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 (BMVC, 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; et al. (CoLLAs, 2022)

Online Continual Learning for Embedded Devices. - Tyler L. Hayes; Christopher Kanan (CoLLAs, 2022)

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 (AAAI Bridge Program, 2023)

How Efficient Are Today's Continual Learning Algorithms? - Md Yousuf Harun; Jhair Gallardo; Tyler L. Hayes; Christopher Kanan (CVPR Workshops, 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)

PANDAS: Prototype-based Novel Class Discovery and Detection. - Tyler L. Hayes; César Roberto de Souza; Namil Kim; Jiwon Kim; Riccardo Volpi; Diane Larlus (CoLLAs, 2024)

SHiNe: Semantic Hierarchy Nexus for Open-Vocabulary Object Detection. - Mingxuan Liu; Tyler L. Hayes; Elisa Ricci 001; Gabriela Csurka; Riccardo Volpi (CVPR, 2024)

What Could Go Wrong? Discovering and Describing Failure Modes in Computer Vision. - Gabriela Csurka; Tyler L. Hayes; Diane Larlus; Riccardo Volpi (ECCV Workshops (21), 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; et al. (Trans. Mach. Learn. Res., 2024)

Test-time Vocabulary Adaptation for Language-driven Object Detection. - Mingxuan Liu; Tyler L. Hayes; Massimiliano Mancini; Elisa Ricci 001; Riccardo Volpi; Gabriela Csurka (CoRR, 2025)