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Architectures

27,448 papers (33 classified directly here)

Subtopics

Neural Networks (11,723) Transformers (10,397) Graph Neural Networks (4,522) Autoencoders (1,154) Convolutional Neural Networks (973) Recurrent Neural Networks (593) Generative Adversarial Networks (18) Encoder-Decoder (14)

Papers per year

27
213
2915
3174
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Papers (including subtopics)

ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task SEMEVAL 2018
YNU-HPCC at Semeval-2018 Task 11: Using an Attention-based CNN-LSTM for Machine Comprehension using Commonsense Knowledge SEMEVAL 2018
Jiangnan at SemEval-2018 Task 11: Deep Neural Network with Attention Method for Machine Comprehension Task SEMEVAL 2018
Lyb3b at SemEval-2018 Task 11: Machine Comprehension Task using Deep Learning Models SEMEVAL 2018
SNU_IDS at SemEval-2018 Task 12: Sentence Encoder with Contextualized Vectors for Argument Reasoning Comprehension SEMEVAL 2018
ITNLP-ARC at SemEval-2018 Task 12: Argument Reasoning Comprehension with Attention SEMEVAL 2018
ECNU at SemEval-2018 Task 12: An End-to-End Attention-based Neural Network for the Argument Reasoning Comprehension Task SEMEVAL 2018
BLCU_NLP at SemEval-2018 Task 12: An Ensemble Model for Argument Reasoning Based on Hierarchical Attention SEMEVAL 2018
YNU Deep at SemEval-2018 Task 12: A BiLSTM Model with Neural Attention for Argument Reasoning Comprehension SEMEVAL 2018
Joker at SemEval-2018 Task 12: The Argument Reasoning Comprehension with Neural Attention SEMEVAL 2018
Lyb3b at SemEval-2018 Task 12: Ensemble-based Deep Learning Models for Argument Reasoning Comprehension Task SEMEVAL 2018
TRANSRW at SemEval-2018 Task 12: Transforming Semantic Representations for Argument Reasoning Comprehension SEMEVAL 2018
Saliency-based Sequential Image Attention with Multiset Prediction NIPS 2017
Deep Hyperalignment NIPS 2017
Recurrent Ladder Networks NIPS 2017
Learning Spherical Convolution for Fast Features from 360° Imagery NIPS 2017
Nonlinear random matrix theory for deep learning NIPS 2017
Spherical convolutions and their application in molecular modelling NIPS 2017
Introspective Classification with Convolutional Nets NIPS 2017
Neural Variational Inference and Learning in Undirected Graphical Models NIPS 2017
Premise Selection for Theorem Proving by Deep Graph Embedding NIPS 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? NIPS 2017
Reconstruct & Crush Network NIPS 2017
Predictive State Recurrent Neural Networks NIPS 2017
Dynamic Routing Between Capsules NIPS 2017