Unsupervised Pre-training
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Benchmarks
Measles
UCI measles
Most implemented
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
Leveraging Pre-trained Checkpoints for Sequence Generation Tasks
wav2vec: Unsupervised Pre-training for Speech Recognition
A Transformer-based Framework for Multivariate Time Series Representation Learning
How far can we go without convolution: Improving fully-connected networks
Papers
Unsupervised Multidomain Approaches to Named Entity Recognition with Small Datasets
This paper explores the challenges and the methodologies associated with learning quality representations in scenarios with unlabelled small or limited datasets for downstream information extraction task (Multidomain Nam…
Unsupervised Pre-trainingInformation ExtractionData AugmentationTransfer LearningFrom Pixels to Temporal Correlations: Learning Informative Representations for Reinforcement Learning Pre-training
Unsupervised pre-training on large-scale datasets has demonstrated significant potential for improving the sample efficiency and performance of Reinforcement Learning (RL). Given the large-scale action-free internet vide…
Unsupervised Pre-trainingReinforcement LearningImage ReconstructionContrastive LearningPolarMAE: Efficient Fetal Ultrasound Pre-training via Semantic Screening and Polar-Guided Masking
Intelligent fetal ultrasound (US) interpretation is crucial for prenatal diagnosis, but high annotation costs and operator-induced variance make unsupervised pre-training a highly promising paradigm. However, existing pr…
Unsupervised Pre-trainingAttribution as Retrieval: Model-Agnostic AI-Generated Image Attribution
With the rapid advancement of AIGC technologies, image forensics will encounter unprecedented challenges. Traditional methods are incapable of dealing with increasingly realistic images generated by rapidly evolving imag…
Unsupervised Pre-trainingImage ClassificationDeepFake DetectionImage AttributionUnsupervised Learning of Efficient Exploration: Pre-training Adaptive Policies via Self-Imposed Goals
Unsupervised pre-training can equip reinforcement learning agents with prior knowledge and accelerate learning in downstream tasks. A promising direction, grounded in human development, investigates agents that learn by …
Unsupervised Pre-trainingReinforcement LearningCommunity Norms in the Spotlight: Enabling Task-Agnostic Unsupervised Pre-Training to Benefit Online Social Media
Modelling the complex dynamics of online social platforms is critical for addressing challenges such as hate speech and misinformation. While Discussion Transformers, which model conversations as graph structures, have e…
Unsupervised Pre-training