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29
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ShareScore release 0.9.0
Dataset results
29 results for “Continual Learning”
ViLCo: VIdeo Language COntinual learning Benchmark
<p>We introduce the first <strong>VIdeo Language COntinual learning Benchmark (ViLCo-Bench). </strong>Video language continual learning involves continuously adapting to information from video and text inputs, enhancing a model’s ability to handle new tasks while retaining prior knowledge. This field is a relatively under-explored area, and establishing appropriate datasets is crucial for facilitating communication and research in this field. In this study, we present the first dedicated benchmark, ViLCo-Bench, designed to evaluate continual learning models across a range of video-text tasks. The dataset comprises ten-minute-long videos and corresponding language queries collected from publicly available datasets.</p> <p>Additionally, we introduce a novel memory-efficient framework that incorporates self-supervised learning and mimics long-term and short-term memory effects. This framework addresses challenges including memory complexity from long video clips, natural language complexity from open queries, and text-video misalignment. We posit that ViLCo-Bench, with greater complexity compared to existing continual learning benchmarks, would serve as a critical tool for exploring the video-language domain, extending beyond conventional class-incremental tasks, and addressing complex and limited annotation issues.</p> <p>More detailed information can also be found on our url: https://github.com/cruiseresearchgroup/ViLCo</p>
Web-Based Intervention Designed to Educate and Improve Adherence Through Learning to Use Continuous Glucose Monitoring
ClinicalTrials.gov study NCT03367351. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Learning from the past to prepare for the future: felids face continued threat from declining prey richness
Open the record for dataset details and reuse information.
Impact of Usability on Continuance Usage Intention in Language Learning Apps with Gamification Features
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Does the Continuous Repetition of Motor Skills at a Consistent Speed With Music Affect Children's Decision-Making and Learning Abilities?
ClinicalTrials.gov study NCT07147686. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
A Study to Learn How Well a Monitoring System Called Continuous Glucose Monitoring (CGM) Which Measures Glucose on an Ongoing Basis Works and How Safe it is in Chinese Patients in Usual Practice
ClinicalTrials.gov study NCT05038761. IPD Sharing: NO. Countries: 1. Publications: 0.
A Machine Learning Approach to Continuous Vital Sign Data Analysis
ClinicalTrials.gov study NCT01448161. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Revisiting Machine Learning based Test Case Prioritization for Continuous Integration
<p>Aborted version</p>
Revisiting Machine Learning based Test Case Prioritization for Continuous Integration
<p>This repository contains a replication package for a research paper submitted to the 45th International Conference on Software Engineering (https://conf.researchr.org/home/icse-2023). We provide our code, data, and result for the ease of replicating our experiments.</p> <p><strong>Code</strong></p> <ul> <li>In the <strong>collect_data</strong> subdirectory, scripts for constructing TCP datasets are provided. We do dependency analysis using Understand (https://www.scitools.com/), so please download the related tools in advance.</li> <li>In the<strong> rl</strong> subdirectory, we provide the python implementation for algorithms RL, COLEMAN, PPO2-PO, ACER-PA, PPO1-LI.</li> <li>In the <strong>supervised_learning</strong> subdirectory, we provide implementations for MART, RankNet, RankBoost, CA, L-MART, which mainly rely on Ranklib (https://sourceforge.net/p/lemur/wiki/RankLib/.). We also provide implementation for DeepOrder.</li> </ul> <p><strong>Data</strong></p> <ul> <li>The <strong>origin</strong> subdirectory contains the original datasets collected from github using our scripts, including 11 projects.</li> <li>The <strong>smote</strong> subdirectory contains the datasets pre-processed by SMOTE.</li> </ul> <p><strong>Result</strong></p> <ul> <li>Results for <strong>RQ1</strong>, <strong>RQ2</strong>, <strong>RQ3</strong>, and <strong>threats to validity</strong> are provided in the corresponding subdirectories. Scripts for plotting figures are also provided.</li> </ul> <p><strong>Reference</strong></p> <p>We adopt code from previous work</p> <p>Learning-to-Rank vs Ranking-to-Learn: Strategies for Regression Testing in Continuous Integration (https://dl.acm.org/doi/abs/10.1145/3377811.3380369) Github repository: https://github.com/icse20/RT-CI</p> <p>Reinforcement Learning for Test Case Prioritization (https://ieeexplore.ieee.org/abstract/document/9394799) Github repository: https://github.com/moji1/tp_rl</p> <p>DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing (https://ieeexplore.ieee.org/abstract/document/9609187) Github repository: https://github.com/AizazSharif/DeepOrder-ICSME21</p> <p>A Multi-Armed Bandit Approach for Test Case Prioritization in Continuous Integration Environments (https://ieeexplore.ieee.org/abstract/document/9086053) Github repository: https://github.com/jacksonpradolima/coleman4hcs</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.