Deep Learning
78,198 papers (26 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Papers per year
2
5
1
2
47
50
53
51
87
90
125
229
234
453
859
1,652
3,233
5,368
6,434
7,726
8,506
9,951
12,524
14,487
6,029
'5
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Papers (including subtopics)
Unsupervised Pretraining for Sequence to Sequence Learning
EMNLP 2017
Unsupervised Representation Learning Using Convolutional Restricted Boltzmann Machine for Spoof Speech Detection
Interspeech 2017
Unsupervised Transformation Learning via Convex Relaxations
NeurIPS 2017
Unsupervised Video Summarization With Adversarial LSTM Networks
CVPR 2017
UntrimmedNets for Weakly Supervised Action Recognition and Detection
CVPR 2017
Using Context Events in Neural Network Models for Event Temporal Status Identification
IJCNLP 2017
Using Context Information for Dialog Act Classification in DNN Framework
EMNLP 2017
Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications
ACML 2017
Using Explicit Discourse Connectives in Translation for Implicit Discourse Relation Classification
IJCNLP 2017
Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm
EMNLP 2017
Using Ranking-CNN for Age Estimation
CVPR 2017
Using Social Networks to Improve Language Variety Identification with Neural Networks
IJCNLP 2017
Using Target-side Monolingual Data for Neural Machine Translation through Multi-task Learning
EMNLP 2017
Using the Output Embedding to Improve Language Models
EACL 2017
Utilizing Visual Forms of Japanese Characters for Neural Review Classification
IJCNLP 2017
VAE Learning via Stein Variational Gradient Descent
NeurIPS 2017
VAIN: Attentional Multi-agent Predictive Modeling
NeurIPS 2017
Vancouver Welcomes You! Minimalist Location Metonymy Resolution
ACL 2017
Variants of RMSProp and Adagrad with Logarithmic Regret Bounds
ICML 2017
Variational Autoencoded Regression: High Dimensional Regression of Visual Data on Complex Manifold
CVPR 2017
Variational Bayesian Multiple Instance Learning With Gaussian Processes
CVPR 2017
Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering
IJCAI 2017
Variational Dropout Sparsifies Deep Neural Networks
ICML 2017
Variational Inference for Gaussian Process Models with Linear Complexity
NeurIPS 2017
Variational Inference for Sparse and Undirected Models
ICML 2017