Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/Label Propagation

Label Propagation

Reported on 10 benchmarks across 3 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision8 results

Image ClassificationonTiered ImageNet 10-way (1-shot)
Accuracy· 2018-05-25
39.4
best: 65.1 (Transductive CNAPS + FETI)
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning arXiv:1805.10002
Image ClassificationonMini-Imagenet 10-way (5-shot)
Accuracy· 2018-05-25
51.2
best: 85.9 (Transductive CNAPS + FETI)
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning arXiv:1805.10002
Image ClassificationonMini-Imagenet 10-way (1-shot)
Accuracy· 2018-05-25
35.2
best: 68.5 (Transductive CNAPS + FETI)
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning arXiv:1805.10002
Image ClassificationonTiered ImageNet 10-way (5-shot)
Accuracy· 2018-05-25
57.9
best: 80.6 (Transductive CNAPS + FETI)
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning arXiv:1805.10002
Few-Shot Image ClassificationonTiered ImageNet 10-way (1-shot)
Accuracy· 2018-05-25
39.4
best: 65.1 (Transductive CNAPS + FETI)
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning arXiv:1805.10002
Few-Shot Image ClassificationonMini-Imagenet 10-way (5-shot)
Accuracy· 2018-05-25
51.2
best: 85.9 (Transductive CNAPS + FETI)
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning arXiv:1805.10002
Few-Shot Image ClassificationonMini-Imagenet 10-way (1-shot)
Accuracy· 2018-05-25
35.2
best: 68.5 (Transductive CNAPS + FETI)
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning arXiv:1805.10002
Few-Shot Image ClassificationonTiered ImageNet 10-way (5-shot)
Accuracy· 2018-05-25
57.9
best: 80.6 (Transductive CNAPS + FETI)
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning arXiv:1805.10002

Graphs2 results

Node Property Predictiononogbn-arxiv
Number of params
0
best: 1386219488 (SimTeG+TAPE+RevGAT)
Node Property Predictiononogbn-products
Number of params
0
best: 313612207 (Node2vec)