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Prototypical Networks for Few-shot Learning

Prototypical Networks for Few-shot Learning

15 March 2017
Jake C. Snell
Kevin Swersky
R. Zemel
ArXivPDFHTML

Papers citing "Prototypical Networks for Few-shot Learning"

27 / 1,527 papers shown
Title
Task-Agnostic Meta-Learning for Few-shot Learning
Task-Agnostic Meta-Learning for Few-shot Learning
Muhammad Abdullah Jamal
Guo-Jun Qi
M. Shah
52
457
0
20 May 2018
Diverse Few-Shot Text Classification with Multiple Metrics
Diverse Few-Shot Text Classification with Multiple Metrics
Mo Yu
Xiaoxiao Guo
Jinfeng Yi
Shiyu Chang
Saloni Potdar
Yu Cheng
Gerald Tesauro
Haoyu Wang
Bowen Zhou
17
214
0
19 May 2018
Piecewise classifier mappings: Learning fine-grained learners for novel
  categories with few examples
Piecewise classifier mappings: Learning fine-grained learners for novel categories with few examples
Xiu-Shen Wei
Peng Wang
Lingqiao Liu
Chunhua Shen
Jianxin Wu
34
124
0
11 May 2018
Towards a universal neural network encoder for time series
Towards a universal neural network encoder for time series
Joan Serrà
Santiago Pascual
Alexandros Karatzoglou
AI4TS
36
119
0
10 May 2018
Unsupervised Feature Learning via Non-Parametric Instance-level
  Discrimination
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
Zhirong Wu
Yuanjun Xiong
Stella X. Yu
Dahua Lin
SSL
108
3,428
0
05 May 2018
Deep Triplet Ranking Networks for One-Shot Recognition
Deep Triplet Ranking Networks for One-Shot Recognition
Meng Ye
Yuhong Guo
16
36
0
19 Apr 2018
Differentiable plasticity: training plastic neural networks with
  backpropagation
Differentiable plasticity: training plastic neural networks with backpropagation
Thomas Miconi
Jeff Clune
Kenneth O. Stanley
AI4CE
18
153
0
06 Apr 2018
Meta-Learning for Semi-Supervised Few-Shot Classification
Meta-Learning for Semi-Supervised Few-Shot Classification
Mengye Ren
Eleni Triantafillou
S. S. Ravi
Jake C. Snell
Kevin Swersky
J. Tenenbaum
Hugo Larochelle
R. Zemel
SSL
13
1,277
0
02 Mar 2018
Memory-based Parameter Adaptation
Memory-based Parameter Adaptation
Pablo Sprechmann
Siddhant M. Jayakumar
Jack W. Rae
Alexander Pritzel
Adria Puigdomenech Badia
Benigno Uria
Oriol Vinyals
Demis Hassabis
Razvan Pascanu
Charles Blundell
ODL
OOD
VLM
21
101
0
28 Feb 2018
Federated Meta-Learning with Fast Convergence and Efficient
  Communication
Federated Meta-Learning with Fast Convergence and Efficient Communication
Fei Chen
Mi Luo
Zhenhua Dong
Zhenguo Li
Xiuqiang He
FedML
34
390
0
22 Feb 2018
Meta-Reinforcement Learning of Structured Exploration Strategies
Meta-Reinforcement Learning of Structured Exploration Strategies
Abhishek Gupta
Russell Mendonca
YuXuan Liu
Pieter Abbeel
Sergey Levine
OffRL
50
343
0
20 Feb 2018
Instance-based Inductive Deep Transfer Learning by Cross-Dataset
  Querying with Locality Sensitive Hashing
Instance-based Inductive Deep Transfer Learning by Cross-Dataset Querying with Locality Sensitive Hashing
Somnath Basu Roy Chowdhury
K. Annervaz
Ambedkar Dukkipati
22
10
0
16 Feb 2018
Few-Shot Learning with Metric-Agnostic Conditional Embeddings
Few-Shot Learning with Metric-Agnostic Conditional Embeddings
Nathan Hilliard
Lawrence Phillips
Scott Howland
A. Yankov
Court D. Corley
Nathan Oken Hodas
SSL
41
158
0
12 Feb 2018
Local Contrast Learning
Local Contrast Learning
Chuanyun Xu
Yang Zhang
Xin Feng
Yongxin Ge
Yihao Zhang
Jianwu Long
20
0
0
10 Feb 2018
Sometimes You Want to Go Where Everybody Knows your Name
Sometimes You Want to Go Where Everybody Knows your Name
Reuben Brasher
Nat Roth
Justin Wagle
30
0
0
30 Jan 2018
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes
Erin Grant
Chelsea Finn
Sergey Levine
Trevor Darrell
Thomas Griffiths
BDL
31
505
0
26 Jan 2018
Label Efficient Learning of Transferable Representations across Domains
  and Tasks
Label Efficient Learning of Transferable Representations across Domains and Tasks
Zelun Luo
Yuliang Zou
Judy Hoffman
Li Fei-Fei
39
275
0
30 Nov 2017
Learning to Compare: Relation Network for Few-Shot Learning
Learning to Compare: Relation Network for Few-Shot Learning
Flood Sung
Yongxin Yang
Li Zhang
Tao Xiang
Philip Torr
Timothy M. Hospedales
110
4,023
0
16 Nov 2017
Data Augmentation Generative Adversarial Networks
Data Augmentation Generative Adversarial Networks
Antreas Antoniou
Amos Storkey
Harrison Edwards
MedIm
GAN
92
1,068
0
12 Nov 2017
Few-Shot Learning with Graph Neural Networks
Few-Shot Learning with Graph Neural Networks
Victor Garcia Satorras
Joan Bruna
GNN
79
1,231
0
10 Nov 2017
Deep Learning for Case-Based Reasoning through Prototypes: A Neural
  Network that Explains Its Predictions
Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions
Oscar Li
Hao Liu
Chaofan Chen
Cynthia Rudin
40
584
0
13 Oct 2017
How intelligent are convolutional neural networks?
How intelligent are convolutional neural networks?
Zhennan Yan
Xiangmin Zhou
25
11
0
18 Sep 2017
Discriminative k-shot learning using probabilistic models
Discriminative k-shot learning using probabilistic models
Matthias Bauer
Mateo Rojas-Carulla
J. Swiatkowski
Bernhard Schölkopf
Richard Turner
VLM
25
71
0
01 Jun 2017
Recent Advances in Transfer Learning for Cross-Dataset Visual
  Recognition: A Problem-Oriented Perspective
Recent Advances in Transfer Learning for Cross-Dataset Visual Recognition: A Problem-Oriented Perspective
Jing Zhang
Wanqing Li
P. Ogunbona
Dong Xu
OOD
32
46
0
11 May 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
679
11,762
0
09 Mar 2017
Deep Reinforcement Learning: An Overview
Deep Reinforcement Learning: An Overview
Yuxi Li
OffRL
VLM
121
1,508
0
25 Jan 2017
Learning Deep Representations of Fine-grained Visual Descriptions
Learning Deep Representations of Fine-grained Visual Descriptions
Scott E. Reed
Zeynep Akata
Bernt Schiele
Honglak Lee
OCL
VLM
183
840
0
17 May 2016
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