Search Results for author:
Found 7 papers, 6 papers with code
LEDetection: A Simple Framework for Semi-Supervised Few-Shot Object Detection
Few-shot object detection (FSOD) is a challenging problem aimed at detecting novel concepts from few exemplars.
SSLayout360: Semi-Supervised Indoor Layout Estimation From 360deg Panorama
Recent years have seen flourishing research on both semi-supervised learning and 3D room layout reconstruction.
SSLayout360: Semi-Supervised Indoor Layout Estimation from 360-Degree Panorama
Recent years have seen flourishing research on both semi-supervised learning and 3D room layout reconstruction.
Exploring Self-Supervised Regularization for Supervised and Semi-Supervised Learning
Recent advances in semi-supervised learning have shown tremendous potential in overcoming a major barrier to the success of modern machine learning algorithms: access to vast amounts of human-labeled training data.
Multi-Task Graph Autoencoders
We examine two fundamental tasks associated with graph representation learning: link prediction and node classification.
Ranked #1 on
Link Prediction
on Pubmed
(Accuracy metric)
Learning to Make Predictions on Graphs with Autoencoders
We examine two fundamental tasks associated with graph representation learning: link prediction and semi-supervised node classification.
Ranked #46 on
Node Classification
on Pubmed
A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRI
To our knowledge, this is the first application of a fully convolutional neural network architecture for pixel-wise labeling in cardiac magnetic resonance imaging.
