{"id":61,"date":"2018-12-08T23:18:53","date_gmt":"2018-12-09T03:18:53","guid":{"rendered":"http:\/\/sites.nd.edu\/annfranchescalaguna\/?p=61"},"modified":"2018-12-08T23:37:42","modified_gmt":"2018-12-09T03:37:42","slug":"few-shot-learning-results","status":"publish","type":"post","link":"https:\/\/sites.nd.edu\/annfranchescalaguna\/2018\/12\/08\/few-shot-learning-results\/","title":{"rendered":"Few-Shot Learning Results"},"content":{"rendered":"

Here are the results from all few shot learning results for Omniglot and Mini-Imagenet.<\/p>\n

 <\/p>\n

Omniglot Dataset<\/strong><\/p>\n\n\n\n\n\t\n\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t
<\/td>5-Way 1-Shot<\/th>5-Way 5-Shot<\/th>20-Way 1-Shot<\/th>20-Way 5-Shot<\/th>\n<\/tr>\n<\/thead>\n
Matching Network<\/a>
\n<\/td>		98.1<\/td>98.9<\/td>93.8<\/td>98.5<\/td>\n<\/tr>\n
Prototypical Network<\/a><\/td>98.8<\/td>99.7<\/td>96.0<\/td>98.9<\/td>\n<\/tr>\n
Model Agnostic Meta-Learning<\/a><\/td>98.7<\/td>99.9<\/td>95.8<\/td>98.6<\/td>\n<\/tr>\n
Neural Statistician<\/a><\/td>98.1<\/td>99.7<\/td>96.0<\/td>98.9<\/td>\n<\/tr>\n
Siamese Network<\/a><\/td>97.3<\/td>94.9<\/td><\/td><\/td>\n<\/tr>\n
Memory Augmented Neural Network<\/a><\/td>82.8<\/td>94.9<\/td><\/td><\/td>\n<\/tr>\n
Learning to Remember Rare-Events<\/a><\/td>98.4<\/td>99.6<\/td>95.0<\/td>98.6<\/td>\n<\/tr>\n
Relation Network<\/a><\/td>99.6<\/td>99.8<\/td>97.6<\/td>99.1<\/td>\n<\/tr>\n
MetaNet<\/a><\/td>99.0<\/td><\/td>97.0<\/td><\/td>\n<\/tr>\n
Gaussian Prototypical Network<\/a><\/td>99.07<\/td>99.73<\/td>96.94<\/td>99.29<\/td>\n<\/tr>\n
SNAIL<\/a><\/td>99.07<\/td>99.78<\/td>97.64<\/td>99.36<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n

 <\/p>\n

miniImageNet Dataset<\/strong><\/p>\n\n\n\n\n\t\n\n\t\n\t\n\t\n\t\n\t\n\t
<\/td>5-Way 1-Shot<\/th>5-Way 5-Shot<\/th>\n<\/tr>\n<\/thead>\n
Matching Network<\/a>
\n<\/td>		43.6<\/td>55.3<\/td>\n<\/tr>\n
Prototypical Network<\/a><\/td>49.42<\/td>68.20<\/td>\n<\/tr>\n
Model Agnostic Meta-Learning<\/a><\/td>48.7<\/td>63.1<\/td>\n<\/tr>\n
Relation Network<\/a><\/td>50.44<\/td>65.32<\/td>\n<\/tr>\n
MetaNet<\/a><\/td>49.21<\/td><\/td>\n<\/tr>\n
SNAIL<\/a><\/td>55.71<\/td>68.88<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n","protected":false},"excerpt":{"rendered":"

Here are the results from all few shot learning results for Omniglot and Mini-Imagenet.   Omniglot Dataset   miniImageNet Dataset<\/p>\n","protected":false},"author":3230,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[326234],"tags":[],"class_list":["post-61","post","type-post","status-publish","format-standard","hentry","category-research-idea"],"_links":{"self":[{"href":"https:\/\/sites.nd.edu\/annfranchescalaguna\/wp-json\/wp\/v2\/posts\/61","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.nd.edu\/annfranchescalaguna\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.nd.edu\/annfranchescalaguna\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.nd.edu\/annfranchescalaguna\/wp-json\/wp\/v2\/users\/3230"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.nd.edu\/annfranchescalaguna\/wp-json\/wp\/v2\/comments?post=61"}],"version-history":[{"count":3,"href":"https:\/\/sites.nd.edu\/annfranchescalaguna\/wp-json\/wp\/v2\/posts\/61\/revisions"}],"predecessor-version":[{"id":68,"href":"https:\/\/sites.nd.edu\/annfranchescalaguna\/wp-json\/wp\/v2\/posts\/61\/revisions\/68"}],"wp:attachment":[{"href":"https:\/\/sites.nd.edu\/annfranchescalaguna\/wp-json\/wp\/v2\/media?parent=61"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.nd.edu\/annfranchescalaguna\/wp-json\/wp\/v2\/categories?post=61"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.nd.edu\/annfranchescalaguna\/wp-json\/wp\/v2\/tags?post=61"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}