Memory Network:

Most referenced

1. Memory Networks, http://arxiv.org/pdf/1410.391…

2. End-To-End Memory Networks, http://papers.nips.cc/paper/5…

3. Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks, http://arxiv.org/pdf/1502.056…

4. Large-scale Simple Question Answering with Memory Networks, http://arxiv.org/pdf/1506.020…

5. Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems, http://arxiv.org/pdf/1511.069…

6. The Goldilocks Principle: Reading Children’s Books with Explicit Memory Representations, http://arxiv.org/pdf/1511.023…

7. Learning End-to-End Goal-Oriented Dialog, http://arxiv.org/pdf/1605.076…

ICML2016

1. Ask Me Anything: Dynamic Memory Networks for Natural Language Processing, http://arxiv.org/pdf/1506.072… 1

2. Meta-Learning with Memory-Augmented Neural Networks, http://jmlr.org/proceedings/p…

3. Associative Long Short-Term Memory, http://arxiv.org/pdf/1602.030…

4. Recurrent Orthogonal Networks and Long-Memory Tasks, http://arxiv.org/pdf/1603.014…

5. Dynamic Memory Networks for Visual and Textual Question Answering, http://arxiv.org/pdf/1603.014…

6. Control of Memory, Active Perception, and Action in Minecraft, http://arxiv.org/pdf/1605.091…

One Shot

CVPR16

1. One-Shot Learning of Scene Locations via Feature Trajectory Transfer, http://www.cv-foundation.org/…

ICML16

1. One-Shot Generalization in Deep Generative Models, https://arxiv.org/pdf/1603.05…

Zero Shot

CVPR16

1. Multi-Cue Zero-Shot Learning With Strong Supervision, http://www.cv-foundation.org/…

2. Latent Embeddings for Zero-Shot Classification, http://arxiv.org/pdf/1603.088…

3. Less Is More: Zero-Shot Learning From Online Textual Documents With Noise Suppression, https://arxiv.org/pdf/1604.01…

4. Synthesized Classifiers for Zero-Shot Learning, https://arxiv.org/pdf/1603.00…

5. Fast Zero-Shot Image Tagging, http://crcv.ucf.edu/papers/cv…

6. Zero-Shot Learning via Joint Latent Similarity Embedding, http://www.cv-foundation.org/…

Unsupervised

Most referenced

1. Unsupervised Learning of Video Representations using LSTMs, http://arxiv.org/pdf/1502.046…

2. Unsupervised Representation Learning With Deep Convolutional Generative Adversarial Networks, https://arxiv.org/pdf/1511.06…

ICML2016

1. A Deep Learning Approach to Unsupervised Ensemble Learning, https://arxiv.org/pdf/1602.02…

2. Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification, http://web.eecs.umich.edu/~ho…

3. Unsupervised Deep Embedding for Clustering Analysis, https://arxiv.org/pdf/1511.06…

CVPR2016

1. Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks, http://www.cv-foundation.org/…

2. Joint Unsupervised Learning of Deep Representations and Image Clusters, http://www.cv-foundation.org/…

Semi/Weakly-supervised

Most referenced

1. Semi-supervised Sequence Learning, https://arxiv.org/pdf/1511.01…

2. Semi-supervised Learning with Deep Generative Models, https://arxiv.org/pdf/1406.52…

ICML2016

1. Weakly- and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation, https://arxiv.org/pdf/1502.02…

CVPR2016

1. NetVLAD: CNN architecture for weakly supervised place recognition, http://www.cv-foundation.org/…

2. Weakly Supervised Deep Detection Networks, https://arxiv.org/pdf/1511.02…

3. WELDON: Weakly Supervised Learning of Deep Convolutional Neural
   Networks, http://webia.lip6.fr/~durandt…

4. Weakly Supervised Object Boundaries, http://arxiv.org/pdf/1511.078…

5. Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelledhttp://www.cv-foundation.org/…