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
Self-Supervised Relative Depth Learning for Urban Scene Understanding—0
Semi-supervised Facial Action Unit Intensity Estimation with Contrastive Learning—0
Semi-Supervised Semantic Segmentation of Cell Nuclei via Diffusion-based Large-Scale Pre-Training and Collaborative Learning—0
SLAM: A Unified Encoder for Speech and Language Modeling via Speech-Text Joint Pre-Training—0
SMiRL: Surprise Minimizing RL in Entropic Environments—0
Spiral Contrastive Learning: An Efficient 3D Representation Learning Method for Unannotated CT Lesions—0
SYNFIX: Automatically Fixing Syntax Errors using Compiler Diagnostics—0
Synthetic vascular structure generation for unsupervised pre-training in CTA segmentation tasks—0
Targeted Forgetting of Image Subgroups in CLIP Models—0
Temporal Autoencoding Improves Generative Models of Time Series—0
Temporal Interpolation as an Unsupervised Pretraining Task for Optical Flow Estimation—0
The Efficiency of Pre-training with Objective Masking in Pseudo Labeling for Semi-Supervised Text Classification—0
Towards General Text Embeddings with Multi-stage Contrastive Learning—0
TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training—0
Transfer Learning for Context-Aware Spoken Language Understanding—0
Transferring self-supervised pre-trained models for SHM data anomaly detection with scarce labeled data—0
Triplet Contrastive Learning for Brain Tumor Classification—0
UHH-LT at SemEval-2019 Task 6: Supervised vs. Unsupervised Transfer Learning for Offensive Language Detection—0
Understanding Semantics from Speech Through Pre-training—0
Unleashing Potential of Unsupervised Pre-Training With Intra-Identity Regularization for Person Re-Identification—0
Unsupervised Active Pre-Training for Reinforcement Learning—0
Unsupervised Deep Feature Extraction for Remote Sensing Image Classification—0
Unsupervised Instance Discriminative Learning for Depression Detection from Speech Signals—0
Unsupervised Learning For Sequence-to-sequence Text-to-speech For Low-resource Languages—0
Unsupervised Learning with Truncated Gaussian Graphical Models—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