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1602.08210
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Architectural Complexity Measures of Recurrent Neural Networks
26 February 2016
Saizheng Zhang
Yuhuai Wu
Tong Che
Zhouhan Lin
Roland Memisevic
Ruslan Salakhutdinov
Yoshua Bengio
GNN
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Papers citing
"Architectural Complexity Measures of Recurrent Neural Networks"
50 / 56 papers shown
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Recurrent Neural Networks for Dynamical Systems: Applications to Ordinary Differential Equations, Collective Motion, and Hydrological Modeling
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Erik Bollt
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Motion Primitives-based Navigation Planning using Deep Collision Prediction
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Paolo De Petris
Kostas Alexis
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10 Jan 2022
Recurrence along Depth: Deep Convolutional Neural Networks with Recurrent Layer Aggregation
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Yanwen Fang
Guodong Li
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Efficient Visual Recognition with Deep Neural Networks: A Survey on Recent Advances and New Directions
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Neural Network Layer Algebra: A Framework to Measure Capacity and Compression in Deep Learning
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A. Banerjee
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Recurrent Neural Network from Adder's Perspective: Carry-lookahead RNN
Haowei Jiang
Fei-wei Qin
Jin Cao
Yong Peng
Yanli Shao
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22 Jun 2021
Parallelizing Legendre Memory Unit Training
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22 Feb 2021
Pruning and Quantization for Deep Neural Network Acceleration: A Survey
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C. Glossner
Lei Wang
Shaobo Shi
Xiaotong Zhang
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Interpreting and Disentangling Feature Components of Various Complexity from DNNs
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Mingjie Li
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Do RNN and LSTM have Long Memory?
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Feiqing Huang
Jia Lv
Yanjie Duan
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Guodong Li
Guangjian Tian
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Depth Enables Long-Term Memory for Recurrent Neural Networks
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A Neural Architecture for Detecting Confusion in Eye-tracking Data
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Convolutional Tensor-Train LSTM for Spatio-temporal Learning
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Wonmin Byeon
Jean Kossaifi
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Jan Kautz
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Temporally Folded Convolutional Neural Networks for Sequence Forecasting
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10 Jan 2020
Gating Revisited: Deep Multi-layer RNNs That Can Be Trained
Mehmet Özgür Türkoglu
Stefano Dáronco
Jan Dirk Wegner
Konrad Schindler
87
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0
25 Nov 2019
Multi-Zone Unit for Recurrent Neural Networks
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Jinchao Zhang
Yang Liu
Jie Zhou
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The Expressivity and Training of Deep Neural Networks: toward the Edge of Chaos?
Gege Zhang
Gang-cheng Li
Ningwei Shen
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Deep Equilibrium Models
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EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks
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Jianru Xue
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Wenjun Zeng
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Nanning Zheng
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R-Transformer: Recurrent Neural Network Enhanced Transformer
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Yao Ma
Zitao Liu
Jiliang Tang
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Discrete Flows: Invertible Generative Models of Discrete Data
Dustin Tran
Keyon Vafa
Kumar Krishna Agrawal
Laurent Dinh
Ben Poole
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24 May 2019
Tiresias: Predicting Security Events Through Deep Learning
Yun Shen
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Deep Landscape Forecasting for Real-time Bidding Advertising
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Jiarui Qin
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Zhengyu Yang
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07 May 2019
Learning to Adaptively Scale Recurrent Neural Networks
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State-Regularized Recurrent Neural Networks
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Representation Mixing for TTS Synthesis
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J. F. Santos
Yoshua Bengio
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48
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Long Short-Term Memory with Dynamic Skip Connections
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Qi Zhang
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Y. Lin
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Character-Level Language Modeling with Deeper Self-Attention
Rami Al-Rfou
Dokook Choe
Noah Constant
Mandy Guo
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09 Aug 2018
Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions
Simone Scardapane
S. Van Vaerenbergh
Danilo Comminiello
Simone Totaro
A. Uncini
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11 Jul 2018
On Training Recurrent Networks with Truncated Backpropagation Through Time in Speech Recognition
Hao Tang
James R. Glass
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Detecting Cyberattacks in Industrial Control Systems Using Convolutional Neural Networks
Moshe Kravchik
A. Shabtai
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Image Super-Resolution via Dual-State Recurrent Networks
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Shiyu Chang
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The unreasonable effectiveness of the forget gate
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An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
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J. Zico Kolter
V. Koltun
DRL
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04 Mar 2018
Nested LSTMs
Joel Ruben Antony Moniz
David M. Krueger
62
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ACtuAL: Actor-Critic Under Adversarial Learning
Anirudh Goyal
Nan Rosemary Ke
Alex Lamb
R. Devon Hjelm
C. Pal
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13 Nov 2017
Wider and Deeper, Cheaper and Faster: Tensorized LSTMs for Sequence Learning
Zhen He
Shaobing Gao
Liang Xiao
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Hangen He
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Dilated Recurrent Neural Networks
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Xiaoxiao Guo
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Xiaodong Cui
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M. Hasegawa-Johnson
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Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks
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Brendan Jou
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Jordi Torres
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Deep Architectures for Neural Machine Translation
Antonio Valerio Miceli Barone
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Barry Haddow
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Bayesian LSTMs in medicine
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Recurrent Additive Networks
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An overview and comparative analysis of Recurrent Neural Networks for Short Term Load Forecasting
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Te-Lin Wu
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Bokui (William) Shen
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Variable Computation in Recurrent Neural Networks
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Multiplicative LSTM for sequence modelling
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Multiplex visibility graphs to investigate recurrent neural networks dynamics
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Hierarchical Multiscale Recurrent Neural Networks
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Sungjin Ahn
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0
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