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 171–180 of 265 papers

TitleStatusHype
Convergence of gradient based pre-training in Denoising autoencoders—0
Corruption Is Not All Bad: Incorporating Discourse Structure into Pre-training via Corruption for Essay Scoring—0
Beyond Fine-Tuning: Transferring Behavior in Reinforcement Learning—0
Cross-Domain Training for Goal-Oriented Conversational Agents—0
CUPre: Cross-domain Unsupervised Pre-training for Few-Shot Cell Segmentation—0
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
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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