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Architectural Complexity Measures of Recurrent Neural Networks
v1v2v3 (latest)

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
ArXiv (abs)PDFHTML

Papers citing "Architectural Complexity Measures of Recurrent Neural Networks"

50 / 64 papers shown
Do Transformer World Models Give Better Policy Gradients?
Do Transformer World Models Give Better Policy Gradients?
Michel Ma
Tianwei Ni
Clement Gehring
P. DÓro
Pierre-Luc Bacon
331
7
0
07 Feb 2024
State-Regularized Recurrent Neural Networks to Extract Automata and
  Explain Predictions
State-Regularized Recurrent Neural Networks to Extract Automata and Explain PredictionsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Cheng Wang
Carolin (Haas) Lawrence
Mathias Niepert
263
3
0
10 Dec 2022
RF-Next: Efficient Receptive Field Search for Convolutional Neural
  Networks
RF-Next: Efficient Receptive Field Search for Convolutional Neural NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Shanghua Gao
Zhong-Yu Li
Qi Han
Ming-Ming Cheng
Liang Wang
362
46
0
14 Jun 2022
Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs
Towards Theoretical Analysis of Transformation Complexity of ReLU DNNsInternational Conference on Machine Learning (ICML), 2022
Jie Ren
Mingjie Li
Meng Zhou
Shih-Han Chan
Quanshi Zhang
218
4
0
04 May 2022
Recurrent Neural Networks for Dynamical Systems: Applications to
  Ordinary Differential Equations, Collective Motion, and Hydrological Modeling
Recurrent Neural Networks for Dynamical Systems: Applications to Ordinary Differential Equations, Collective Motion, and Hydrological ModelingChaos (Chaos), 2022
Yonggi Park
Kelum Gajamannage
D. Jayathilake
Erik Bollt
AI4CE
297
27
0
14 Feb 2022
Motion Primitives-based Navigation Planning using Deep Collision
  Prediction
Motion Primitives-based Navigation Planning using Deep Collision PredictionIEEE International Conference on Robotics and Automation (ICRA), 2022
Huan Nguyen
Sondre Holm Fyhn
Paolo De Petris
Kostas Alexis
252
31
0
10 Jan 2022
Recurrence along Depth: Deep Convolutional Neural Networks with
  Recurrent Layer Aggregation
Recurrence along Depth: Deep Convolutional Neural Networks with Recurrent Layer AggregationNeural Information Processing Systems (NeurIPS), 2021
Jingyu Zhao
Yanwen Fang
Guodong Li
182
29
0
22 Oct 2021
Temporal Convolutions for Multi-Step Quadrotor Motion Prediction
Temporal Convolutions for Multi-Step Quadrotor Motion PredictionCanadian Conference on Computer and Robot Vision (CRV), 2021
Sam Looper
Steven L. Waslander
249
9
0
08 Oct 2021
Efficient Visual Recognition with Deep Neural Networks: A Survey on
  Recent Advances and New Directions
Efficient Visual Recognition with Deep Neural Networks: A Survey on Recent Advances and New DirectionsMachine Intelligence Research (MIR), 2021
Yang Wu
Dingheng Wang
Xiaotong Lu
Fan Yang
Guoqi Li
Weiming Dong
Jianbo Shi
422
19
0
30 Aug 2021
Neural Network Layer Algebra: A Framework to Measure Capacity and
  Compression in Deep Learning
Neural Network Layer Algebra: A Framework to Measure Capacity and Compression in Deep Learning
Alberto Badías
A. Banerjee
381
6
0
02 Jul 2021
Recurrent Neural Network from Adder's Perspective: Carry-lookahead RNN
Recurrent Neural Network from Adder's Perspective: Carry-lookahead RNNNeural Networks (NN), 2021
Haowei Jiang
Fei-wei Qin
Jin Cao
Yong Peng
Yanli Shao
LRMODL
221
58
0
22 Jun 2021
Parallelizing Legendre Memory Unit Training
Parallelizing Legendre Memory Unit TrainingInternational Conference on Machine Learning (ICML), 2021
Narsimha Chilkuri
C. Eliasmith
306
47
0
22 Feb 2021
Pruning and Quantization for Deep Neural Network Acceleration: A Survey
Pruning and Quantization for Deep Neural Network Acceleration: A SurveyNeurocomputing (Neurocomputing), 2021
Tailin Liang
C. Glossner
Lei Wang
Shaobo Shi
Xiaotong Zhang
MQ
779
921
0
24 Jan 2021
Kronecker CP Decomposition with Fast Multiplication for Compressing RNNs
Kronecker CP Decomposition with Fast Multiplication for Compressing RNNs
Dingheng Wang
Bijiao Wu
Guangshe Zhao
Man Yao
Hengnu Chen
Lei Deng
Tianyi Yan
Guoqi Li
MQ
229
29
0
21 Aug 2020
Interpreting and Disentangling Feature Components of Various Complexity
  from DNNs
Interpreting and Disentangling Feature Components of Various Complexity from DNNs
Jie Ren
Mingjie Li
Zexu Liu
Quanshi Zhang
CoGe
341
20
0
29 Jun 2020
Do RNN and LSTM have Long Memory?
Do RNN and LSTM have Long Memory?
Jingyu Zhao
Feiqing Huang
Jia Lv
Yanjie Duan
Zhen Qin
Guodong Li
Guangjian Tian
282
183
0
06 Jun 2020
Depth Enables Long-Term Memory for Recurrent Neural Networks
Depth Enables Long-Term Memory for Recurrent Neural Networks
A. Ziv
157
0
0
23 Mar 2020
A Neural Architecture for Detecting Confusion in Eye-tracking Data
A Neural Architecture for Detecting Confusion in Eye-tracking Data
Shane D. V. Sims
Cristina Conati
131
2
0
13 Mar 2020
Convolutional Tensor-Train LSTM for Spatio-temporal Learning
Convolutional Tensor-Train LSTM for Spatio-temporal LearningNeural Information Processing Systems (NeurIPS), 2020
Jiahao Su
Wonmin Byeon
Jean Kossaifi
Furong Huang
Jan Kautz
Anima Anandkumar
AI4TS
489
140
0
21 Feb 2020
Temporally Folded Convolutional Neural Networks for Sequence Forecasting
Temporally Folded Convolutional Neural Networks for Sequence Forecasting
Matthias Weissenbacher
AI4TS
148
0
0
10 Jan 2020
Gating Revisited: Deep Multi-layer RNNs That Can Be Trained
Gating Revisited: Deep Multi-layer RNNs That Can Be TrainedIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
Mehmet Özgür Türkoglu
Stefano Dáronco
Jan Dirk Wegner
Konrad Schindler
574
64
0
25 Nov 2019
Multi-Zone Unit for Recurrent Neural Networks
Multi-Zone Unit for Recurrent Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2019
Fandong Meng
Jinchao Zhang
Yang Liu
Jie Zhou
AI4CE
214
2
0
17 Nov 2019
The Expressivity and Training of Deep Neural Networks: toward the Edge
  of Chaos?
The Expressivity and Training of Deep Neural Networks: toward the Edge of Chaos?
Gege Zhang
Gang-cheng Li
Ningwei Shen
Weidong Zhang
232
7
0
11 Oct 2019
Deep Equilibrium Models
Deep Equilibrium ModelsNeural Information Processing Systems (NeurIPS), 2019
Shaojie Bai
J. Zico Kolter
V. Koltun
346
838
0
03 Sep 2019
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural NetworksIEEE Transactions on Image Processing (TIP), 2019
Pengfei Zhang
Jianru Xue
Cuiling Lan
Wenjun Zeng
Zhanning Gao
Nanning Zheng
192
93
0
03 Sep 2019
Approximating Stacked and Bidirectional Recurrent Architectures with the
  Delayed Recurrent Neural Network
Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network
Javier S. Turek
Shailee Jain
Vy A. Vo
Mihai Capota
Alexander G. Huth
Theodore L. Willke
239
3
0
30 Aug 2019
R-Transformer: Recurrent Neural Network Enhanced Transformer
R-Transformer: Recurrent Neural Network Enhanced Transformer
Z. Wang
Yao Ma
Zitao Liu
Shucheng Zhou
ViT
277
116
0
12 Jul 2019
Discrete Flows: Invertible Generative Models of Discrete Data
Discrete Flows: Invertible Generative Models of Discrete Data
Dustin Tran
Keyon Vafa
Kumar Krishna Agrawal
Laurent Dinh
Ben Poole
DRL
387
128
0
24 May 2019
Tiresias: Predicting Security Events Through Deep Learning
Tiresias: Predicting Security Events Through Deep LearningConference on Computer and Communications Security (CCS), 2018
Yun Shen
Enrico Mariconti
Pierre-Antoine Vervier
Gianluca Stringhini
AAML
204
180
0
24 May 2019
Deep Landscape Forecasting for Real-time Bidding Advertising
Deep Landscape Forecasting for Real-time Bidding AdvertisingKnowledge Discovery and Data Mining (KDD), 2019
Kan Ren
Jiarui Qin
Lei Zheng
Zhengyu Yang
Weinan Zhang
Yong Yu
OOD
236
43
0
07 May 2019
Learning to Adaptively Scale Recurrent Neural Networks
Learning to Adaptively Scale Recurrent Neural Networks
Hao Hu
Liqiang Wang
Guo-Jun Qi
AI4CE
166
11
0
15 Feb 2019
State-Regularized Recurrent Neural Networks
State-Regularized Recurrent Neural Networks
Cheng Wang
Mathias Niepert
235
44
0
25 Jan 2019
Representation Mixing for TTS Synthesis
Representation Mixing for TTS SynthesisIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2018
Kyle Kastner
J. F. Santos
Yoshua Bengio
Aaron Courville
243
46
0
17 Nov 2018
Long Short-Term Memory with Dynamic Skip Connections
Long Short-Term Memory with Dynamic Skip ConnectionsAAAI Conference on Artificial Intelligence (AAAI), 2018
Tao Gui
Tao Gui
Lujun Zhao
Y. Lin
Minlong Peng
Jingjing Gong
Xuanjing Huang
208
31
0
09 Nov 2018
Character-Level Language Modeling with Deeper Self-Attention
Character-Level Language Modeling with Deeper Self-Attention
Rami Al-Rfou
Dokook Choe
Noah Constant
Mandy Guo
Llion Jones
464
416
0
09 Aug 2018
MCRM: Mother Compact Recurrent Memory
MCRM: Mother Compact Recurrent Memory
Abduallah A. Mohamed
Christian G. Claudel
188
1
0
04 Aug 2018
Recurrent Neural Networks with Flexible Gates using Kernel Activation
  Functions
Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions
Simone Scardapane
S. Van Vaerenbergh
Danilo Comminiello
Simone Totaro
A. Uncini
141
4
0
11 Jul 2018
On Training Recurrent Networks with Truncated Backpropagation Through
  Time in Speech Recognition
On Training Recurrent Networks with Truncated Backpropagation Through Time in Speech Recognition
Hao Tang
James R. Glass
203
22
0
09 Jul 2018
Detecting Cyberattacks in Industrial Control Systems Using Convolutional
  Neural Networks
Detecting Cyberattacks in Industrial Control Systems Using Convolutional Neural Networks
Moshe Kravchik
A. Shabtai
230
316
0
21 Jun 2018
Image Super-Resolution via Dual-State Recurrent Networks
Image Super-Resolution via Dual-State Recurrent Networks
Wei Han
Shiyu Chang
Ding Liu
Mo Yu
Michael Witbrock
Thomas S. Huang
SupR
317
238
0
07 May 2018
The unreasonable effectiveness of the forget gate
The unreasonable effectiveness of the forget gate
J. Westhuizen
Joan Lasenby
267
98
0
13 Apr 2018
An Empirical Evaluation of Generic Convolutional and Recurrent Networks
  for Sequence Modeling
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
Shaojie Bai
J. Zico Kolter
V. Koltun
DRL
470
6,378
0
04 Mar 2018
Nested LSTMs
Nested LSTMs
Joel Ruben Antony Moniz
David M. Krueger
250
70
0
31 Jan 2018
ACtuAL: Actor-Critic Under Adversarial Learning
ACtuAL: Actor-Critic Under Adversarial Learning
Anirudh Goyal
Nan Rosemary Ke
Alex Lamb
R. Devon Hjelm
C. Pal
Joelle Pineau
Yoshua Bengio
GAN
143
9
0
13 Nov 2017
Wider and Deeper, Cheaper and Faster: Tensorized LSTMs for Sequence
  Learning
Wider and Deeper, Cheaper and Faster: Tensorized LSTMs for Sequence Learning
Zhen He
Shaobing Gao
Liang Xiao
Daxue Liu
Hangen He
David Barber
AIMat
401
67
0
05 Nov 2017
Dilated Recurrent Neural Networks
Dilated Recurrent Neural Networks
Shiyu Chang
Yang Zhang
Wei Han
Mo Yu
Xiaoxiao Guo
Wei Tan
Xiaodong Cui
Michael Witbrock
M. Hasegawa-Johnson
Thomas S. Huang
424
345
0
05 Oct 2017
Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks
Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks
Victor Campos
Brendan Jou
Xavier Giró-i-Nieto
Jordi Torres
Shih-Fu Chang
411
229
0
22 Aug 2017
Deep Architectures for Neural Machine Translation
Deep Architectures for Neural Machine Translation
Antonio Valerio Miceli Barone
Jindřich Helcl
Rico Sennrich
Barry Haddow
Alexandra Birch
190
113
0
24 Jul 2017
Bayesian LSTMs in medicine
Bayesian LSTMs in medicine
J. Westhuizen
Joan Lasenby
BDLOOD
149
17
0
05 Jun 2017
Techniques for visualizing LSTMs applied to electrocardiograms
Techniques for visualizing LSTMs applied to electrocardiograms
J. Westhuizen
Joan Lasenby
AI4TS
216
5
0
23 May 2017
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