{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T19:40:00Z","timestamp":1767987600234,"version":"3.49.0"},"reference-count":61,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T00:00:00Z","timestamp":1696204800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T00:00:00Z","timestamp":1696204800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,10,2]]},"DOI":"10.1109\/iccvw60793.2023.00359","type":"proceedings-article","created":{"date-parts":[[2023,12,25]],"date-time":"2023-12-25T14:31:40Z","timestamp":1703514700000},"page":"3337-3347","source":"Crossref","is-referenced-by-count":5,"title":["ScrollNet: Dynamic Weight Importance for Continual Learning"],"prefix":"10.1109","author":[{"given":"Fei","family":"Yang","sequence":"first","affiliation":[{"name":"Universitat Aut&#x00F2;noma de Barcelona,Computer Vision Center,Barcelona,Spain"}]},{"given":"Kai","family":"Wang","sequence":"additional","affiliation":[{"name":"Universitat Aut&#x00F2;noma de Barcelona,Computer Vision Center,Barcelona,Spain"}]},{"given":"Joost","family":"van de Weijer","sequence":"additional","affiliation":[{"name":"Universitat Aut&#x00F2;noma de Barcelona,Computer Vision Center,Barcelona,Spain"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00399"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01219-9_9"},{"key":"ref3","article-title":"Estimating or propagating gradients through stochastic neurons for conditional computation","author":"Bengio","year":"2013"},{"key":"ref4","first-page":"527","article-title":"Adaptive neural networks for efficient inference","volume-title":"International Conference on Machine Learning","author":"Bolukbasi"},{"key":"ref5","first-page":"15920","article-title":"Dark experience for general continual learning: a strong, simple baseline","volume":"33","author":"Buzzega","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref6","article-title":"Efficient lifelong learning with a-gem","volume-title":"International Conference on Learning Representations","author":"Chaudhry"},{"key":"ref7","article-title":"On tiny episodic memories in continual learning","author":"Chaudhry","year":"2019"},{"key":"ref8","article-title":"Exponentially increasing the capacity-to-computation ratio for conditional computation in deep learning","author":"Cho","year":"2014"},{"key":"ref9","article-title":"A continual learning survey: Defying forgetting in classification tasks","volume-title":"IEEE TPAMI","author":"De Lange"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3057446"},{"key":"ref11","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2020"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00403"},{"key":"ref13","article-title":"Learning factored representations in a deep mixture of experts","author":"Eigen","year":"2013"},{"key":"ref14","article-title":"Distilling a neural network into a soft decision tree","author":"Frosst","year":"2017"},{"key":"ref15","article-title":"Adaptive computation time for recurrent neural networks","author":"Graves","year":"2016"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3117837"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58598-3_28"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00092"},{"key":"ref20","article-title":"Multi-scale dense networks for resource efficient image classification","author":"Huang","year":"2017"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1991.3.1.79"},{"key":"ref22","first-page":"3301","article-title":"Shallow-deep networks: Understanding and mitigating network overthinking","volume-title":"International conference on machine learning","author":"Kaya"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1611835114"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19809-0_13"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.172"},{"key":"ref26","author":"Krizhevsky","year":"2009","journal-title":"Learning multiple layers of features from tiny images"},{"issue":"7","key":"ref27","first-page":"3","article-title":"Tiny imagenet visual recognition challenge","volume":"7","author":"Le","year":"2015","journal-title":"CS 231N"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2773081"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11630"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00121"},{"key":"ref31","article-title":"Gradient episodic memory for continual learning","volume":"30","author":"Lopez-Paz","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01225-0_5"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00810"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3213473"},{"key":"ref35","article-title":"Ternary feature masks: continual learning without any forgetting","volume-title":"2nd CLVISION workshop in CVPR 2021","author":"Masana"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1803839115"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/s0079-7421(08)60536-8"},{"key":"ref38","first-page":"100","article-title":"Continual learning using a bayesian nonparametric dictionary of weight factors","volume-title":"International Conference on Artificial Intelligence and Statistics","author":"Mehta"},{"key":"ref39","first-page":"7308","article-title":"Understanding the role of training regimes in continual learning","volume":"33","author":"Mirzadeh","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref40","article-title":"Changing model behavior at test-time using reinforcement learning","author":"Odena","year":"2017"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.01.012"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.587"},{"key":"ref43","article-title":"Learning to learn without forgetting by maximizing transfer and minimizing interference","volume-title":"International Conference on Learning Representations","author":"Riemer"},{"key":"ref44","article-title":"Progressive neural networks","author":"Rusu","year":"2016"},{"key":"ref45","first-page":"4548","article-title":"Overcoming catastrophic forgetting with hard attention to the task","volume-title":"International Conference on Machine Learning","author":"Serra"},{"key":"ref46","first-page":"2994","article-title":"Continual learning with deep generative replay","volume-title":"NeurIPS","author":"Shin"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00951"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2016.7900006"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_1"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2023.02.001"},{"key":"ref51","article-title":"Continual learning with hypernetworks","author":"Von Oswald","year":"2019"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00025"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_25"},{"key":"ref54","first-page":"2516","article-title":"Zero time waste: Recycling predictions in early exit neural networks","volume":"34","author":"Wo\u0142czyk","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref55","first-page":"15173","article-title":"Supermasks in superposition","volume":"33","author":"Wortsman","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref56","first-page":"5962","article-title":"Memory replay gans: Learn ing to generate new categories without forgetting","volume":"31","author":"Wu","year":"2018","journal-title":"NeurIPS"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00046"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00496"},{"key":"ref59","article-title":"Slimmable neural networks","volume-title":"International Conference on Learning Representations","author":"Yu"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3155746"},{"key":"ref61","first-page":"3987","volume-title":"Continual learning through synaptic intelligence","author":"Zenke","year":"2017"}],"event":{"name":"2023 IEEE\/CVF International Conference on Computer Vision Workshops (ICCVW)","location":"Paris, France","start":{"date-parts":[[2023,10,2]]},"end":{"date-parts":[[2023,10,6]]}},"container-title":["2023 IEEE\/CVF International Conference on Computer Vision Workshops (ICCVW)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10350357\/10350360\/10350538.pdf?arnumber=10350538","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T22:01:47Z","timestamp":1705010507000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10350538\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,2]]},"references-count":61,"URL":"https:\/\/doi.org\/10.1109\/iccvw60793.2023.00359","relation":{},"subject":[],"published":{"date-parts":[[2023,10,2]]}}}