SOTAVerified

Unsupervised Pre-training

Pre-training a neural network using unsupervised (self-supervised) auxiliary tasks on unlabeled data.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 176–200 of 265 papers

TitleStatusHype
Deep Belief Networks Based Feature Generation and Regression for Predicting Wind Power—0
Deep Discriminative Model for Video Classification—0
Deep Features for CBIR with Scarce Data using Hebbian Learning—0
Device Tuning for Multi-Task Large Model—0
Discovery of Visual Semantics by Unsupervised and Self-Supervised Representation Learning—0
DiscrimNet: Semi-Supervised Action Recognition from Videos using Generative Adversarial Networks—0
Disentangling Node Attributes from Graph Topology for Improved Generalizability in Link Prediction—0
DPER: Diffusion Prior Driven Neural Representation for Limited Angle and Sparse View CT Reconstruction—0
Differentially Private Optimization for Non-Decomposable Objective Functions—0
ECGBERT: Understanding Hidden Language of ECGs with Self-Supervised Representation Learning—0
Effective training of deep convolutional neural networks for hyperspectral image classification through artificial labeling—0
Empirical Evaluation of Active Learning Techniques for Neural MT—0
Enhance Visual Recognition under Adverse Conditions via Deep Networks—0
Enhancing the vocal range of single-speaker singing voice synthesis with melody-unsupervised pre-training—0
ERNIE at SemEval-2020 Task 10: Learning Word Emphasis Selection by Pre-trained Language Model—0
EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model—0
Evaluate Confidence Instead of Perplexity for Zero-shot Commonsense Reasoning—0
Examining the Effect of Pre-training on Time Series Classification—0
Exploiting Unsupervised Pre-training and Automated Feature Engineering for Low-resource Hate Speech Detection in Polish—0
ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts—0
Extracting UMLS Concepts from Medical Text Using General and Domain-Specific Deep Learning Models—0
Extractive NarrativeQA with Heuristic Pre-Training—0
Generalized 3D Self-supervised Learning Framework via Prompted Foreground-Aware Feature Contrast—0
FairSISA: Ensemble Post-Processing to Improve Fairness of Unlearning in LLMs—0
Faster learning of deep stacked autoencoders on multi-core systems using synchronized layer-wise pre-training—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
115RDLsAccuracy (%)95—Unverified
29RDLsAccuracy (%)94—Unverified
33 RMDLAccuracy (%)93—Unverified
4CNNAccuracy (%)73—Unverified
5RMDLAccuracy (%)0.1—Unverified
#ModelMetricClaimedVerifiedStatus
1RMDL (30 RDLs)Sensitivity (VEB)90.69—Unverified
2Sensitivity89.1—Unverified
3RMDL 3 RDLsSensitivity0.87—Unverified