SOTAVerified

Auxiliary Learning

Auxiliary learning aims to find or design auxiliary tasks which can improve the performance on one or some primary tasks.

( Image credit: Self-Supervised Generalisation with Meta Auxiliary Learning )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 11–20 of 100 papers

TitleStatusHype
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference CostCode0
Meta-Auxiliary Learning for Micro-Expression Recognition—0
HiMAL: A Multimodal Hierarchical Multi-task Auxiliary Learning framework for predicting and explaining Alzheimer disease progression—0
GeoAuxNet: Towards Universal 3D Representation Learning for Multi-sensor Point CloudsCode1
Learning Multiple Representations with Inconsistency-Guided Detail Regularization for Mask-Guided Matting—0
Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation—0
Two-Stage Multi-task Self-Supervised Learning for Medical Image Segmentation—0
Enhancing Molecular Property Prediction with Auxiliary Learning and Task-Specific AdaptationCode0
A Survey on Cross-Domain Sequential RecommendationCode1
Fast Adaptation for Human Pose Estimation via Meta-Optimization—0
Show:102550
← PrevPage 2 of 10Next →

No leaderboard results yet.