Neural and Evolutionary Computing

Papers filed under cs.NE on arXiv, each one already summarized by Paperlayer. Open any of them to read the summary beside the original PDF, with every point linked to the line, figure, or table it came from.

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1,621 to 1,680 of 1,835

A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations
Shengxian Wan, Yanyan Lan, Jiafeng Guo +3
cs.AIcs.CLcs.NEarXiv:1511.08277v12015
A guide to convolution arithmetic for deep learning
Vincent Dumoulin, Francesco Visin
stat.MLcs.LGcs.NEarXiv:1603.07285v22016
Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video
Lionel Pigou, Aäron van den Oord, Sander Dieleman +2
cs.CVcs.AIcs.LGarXiv:1506.01911v32015
Transition-Based Dependency Parsing with Stack Long Short-Term Memory
Chris Dyer, Miguel Ballesteros, Wang Ling +2
cs.CLcs.LGcs.NEarXiv:1505.08075v12015
An Implementation of Intrusion Detection System Using Genetic Algorithm
Mohammad Sazzadul Hoque, Md. Abdul Mukit, Md. Abu Naser Bikas
cs.CRcs.NEcs.NIarXiv:1204.1336v12012
Resnet in Resnet: Generalizing Residual Architectures
Sasha Targ, Diogo Almeida, Kevin Lyman
cs.LGcs.CVcs.NEarXiv:1603.08029v12016
A Unified Deep Neural Network for Speaker and Language Recognition
Fred Richardson, Douglas Reynolds, Najim Dehak
cs.CLcs.CVcs.LGarXiv:1504.00923v12015
Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding
Alex Kendall, Vijay Badrinarayanan, Roberto Cipolla
cs.CVcs.NEarXiv:1511.02680v22015
Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition?
Pooya Khorrami, Tom Le Paine, Thomas S. Huang
cs.CVcs.LGcs.NEarXiv:1510.02969v32015
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
Song Han, Huizi Mao, William J. Dally
cs.CVcs.NEarXiv:1510.00149v52015
Going Deeper in Facial Expression Recognition using Deep Neural Networks
Ali Mollahosseini, David Chan, Mohammad H. Mahoor
cs.NEcs.CVarXiv:1511.04110v12015
Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices
Tayfun Gokmen, Yurii Vlasov
cs.LGcs.NEstat.MLarXiv:1603.07341v12016
Structured Pruning of Deep Convolutional Neural Networks
Sajid Anwar, Kyuyeon Hwang, Wonyong Sung
cs.NEcs.LGstat.MLarXiv:1512.08571v12015
Deep convolutional neural networks for predominant instrument recognition in polyphonic music
Yoonchang Han, Jaehun Kim, Kyogu Lee
cs.SDcs.CVcs.LGarXiv:1605.09507v32016
An Introduction to Convolutional Neural Networks
Keiron O'Shea, Ryan Nash
cs.NEcs.CVcs.LGarXiv:1511.08458v22015
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan, Alex Kendall, Roberto Cipolla
cs.CVcs.LGcs.NEarXiv:1511.00561v32015
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks
Peter Ondruska, Ingmar Posner
cs.LGcs.AIcs.CVarXiv:1602.00991v22016
Listen, Attend and Spell
William Chan, Navdeep Jaitly, Quoc V. Le +1
cs.CLcs.LGcs.NEarXiv:1508.01211v22015
Towards Deep Neural Network Architectures Robust to Adversarial Examples
Shixiang Gu, Luca Rigazio
cs.LGcs.CVcs.NEarXiv:1412.5068v42014
Visual7W: Grounded Question Answering in Images
Yuke Zhu, Oliver Groth, Michael Bernstein +1
cs.CVcs.LGcs.NEarXiv:1511.03416v42015
Deep-Plant: Plant Identification with convolutional neural networks
Sue Han Lee, Chee Seng Chan, Paul Wilkin +1
cs.CVcs.AIcs.NEarXiv:1506.08425v12015
Learning to Compare Image Patches via Convolutional Neural Networks
Sergey Zagoruyko, Nikos Komodakis
cs.CVcs.LGcs.NEarXiv:1504.03641v12015
A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification
Ye Zhang, Byron Wallace
cs.CLcs.LGcs.NEarXiv:1510.03820v42015
Memory and information processing in neuromorphic systems
Giacomo Indiveri, Shih-Chii Liu
cs.NEarXiv:1506.03264v12015
Unsupervised Learning of Video Representations using LSTMs
Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov
cs.LGcs.CVcs.NEarXiv:1502.04681v32015
Rotation-invariant convolutional neural networks for galaxy morphology prediction
Sander Dieleman, Kyle W. Willett, Joni Dambre
astro-ph.IMastro-ph.GAcs.CVarXiv:1503.07077v12015
Do Convnets Learn Correspondence?
Jonathan Long, Ning Zhang, Trevor Darrell
cs.CVcs.LGcs.NEarXiv:1411.1091v12014
Transferring Rich Feature Hierarchies for Robust Visual Tracking
Naiyan Wang, Siyi Li, Abhinav Gupta +1
cs.CVcs.NEarXiv:1501.04587v22015
The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems
Ryan Lowe, Nissan Pow, Iulian Serban +1
cs.CLcs.AIcs.LGarXiv:1506.08909v32015
Learning both Weights and Connections for Efficient Neural Networks
Song Han, Jeff Pool, John Tran +1
cs.NEcs.CVcs.LGarXiv:1506.02626v32015
Flattened Convolutional Neural Networks for Feedforward Acceleration
Jonghoon Jin, Aysegul Dundar, Eugenio Culurciello
cs.NEcs.LGarXiv:1412.5474v42014
Inverting Visual Representations with Convolutional Networks
Alexey Dosovitskiy, Thomas Brox
cs.NEcs.CVcs.LGarXiv:1506.02753v42015
Stacked What-Where Auto-encoders
Junbo Zhao, Michael Mathieu, Ross Goroshin +1
stat.MLcs.LGcs.NEarXiv:1506.02351v82015
How transferable are features in deep neural networks?
Jason Yosinski, Jeff Clune, Yoshua Bengio +1
cs.LGcs.NEarXiv:1411.1792v12014
Striving for Simplicity: The All Convolutional Net
Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox +1
cs.LGcs.CVcs.NEarXiv:1412.6806v32014
Spatio-Temporal Backpropagation for Training High-performance Spiking Neural Networks
Yujie Wu, Lei Deng, Guoqi Li +2
cs.NEq-bio.NCstat.MLarXiv:1706.02609v32017
One weird trick for parallelizing convolutional neural networks
Alex Krizhevsky
cs.NEcs.DCcs.LGarXiv:1404.5997v22014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Nguyen, Jason Yosinski, Jeff Clune
cs.CVcs.AIcs.NEarXiv:1412.1897v42014
Long Short-Term Memory Based Recurrent Neural Network Architectures for Large Vocabulary Speech Recognition
Haşim Sak, Andrew Senior, Françoise Beaufays
cs.NEcs.CLcs.LGarXiv:1402.1128v12014
graph2vec: Learning Distributed Representations of Graphs
Annamalai Narayanan, Mahinthan Chandramohan, Rajasekar Venkatesan +3
cs.AIcs.CLcs.CRarXiv:1707.05005v12017
Deep Fried Convnets
Zichao Yang, Marcin Moczulski, Misha Denil +4
cs.LGcs.NEstat.MLarXiv:1412.7149v42014
A Clockwork RNN
Jan Koutník, Klaus Greff, Faustino Gomez +1
cs.NEcs.LGarXiv:1402.3511v12014
Bidirectional Recurrent Neural Networks for Medical Event Detection in Electronic Health Records
Abhyuday Jagannatha, Hong Yu
cs.CLcs.LGcs.NEarXiv:1606.07953v22016
Cuckoo Search: Recent Advances and Applications
Xin-She Yang, Suash Deb
math.OCcs.NEnlin.AOarXiv:1408.5316v12014
Caffe: Convolutional Architecture for Fast Feature Embedding
Yangqing Jia, Evan Shelhamer, Jeff Donahue +5
cs.CVcs.LGcs.NEarXiv:1408.5093v12014
Learning Longer Memory in Recurrent Neural Networks
Tomas Mikolov, Armand Joulin, Sumit Chopra +2
cs.NEcs.LGarXiv:1412.7753v22014
Qualitatively characterizing neural network optimization problems
Ian J. Goodfellow, Oriol Vinyals, Andrew M. Saxe
cs.NEcs.LGstat.MLarXiv:1412.6544v62014
Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks
Yuyu Zhang, Hanjun Dai, Chang Xu +5
cs.IRcs.LGcs.NEarXiv:1404.5772v32014
CMA-ES for Hyperparameter Optimization of Deep Neural Networks
Ilya Loshchilov, Frank Hutter
cs.NEcs.LGarXiv:1604.07269v12016
A comprehensive review of firefly algorithms
Iztok Fister, Iztok Fister, Xin-She Yang +1
cs.NEarXiv:1312.6609v12013
When Face Recognition Meets with Deep Learning: an Evaluation of Convolutional Neural Networks for Face Recognition
Guosheng Hu, Yongxin Yang, Dong Yi +4
cs.CVcs.LGcs.NEarXiv:1504.02351v12015
Dropout improves Recurrent Neural Networks for Handwriting Recognition
Vu Pham, Théodore Bluche, Christopher Kermorvant +1
cs.CVcs.LGcs.NEarXiv:1312.4569v22013
Image Super-Resolution Using Deep Convolutional Networks
Chao Dong, Chen Change Loy, Kaiming He +1
cs.CVcs.NEarXiv:1501.00092v32014
Spectral Networks and Locally Connected Networks on Graphs
Joan Bruna, Wojciech Zaremba, Arthur Szlam +1
cs.LGcs.CVcs.NEarXiv:1312.6203v32013
Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition
Xiangang Li, Xihong Wu
cs.CLcs.NEarXiv:1410.4281v22014
Fast Training of Convolutional Networks through FFTs
Michael Mathieu, Mikael Henaff, Yann LeCun
cs.CVcs.LGcs.NEarXiv:1312.5851v52013
Predicting Parameters in Deep Learning
Misha Denil, Babak Shakibi, Laurent Dinh +2
cs.LGcs.NEstat.MLarXiv:1306.0543v22013
Sequence Transduction with Recurrent Neural Networks
Alex Graves
cs.NEcs.LGstat.MLarXiv:1211.3711v12012
Convolutional Neural Networks Applied to House Numbers Digit Classification
Pierre Sermanet, Soumith Chintala, Yann LeCun
cs.CVcs.LGcs.NEarXiv:1204.3968v12012
The Deterministic Dendritic Cell Algorithm
Julie Greensmith, Uwe Aickelin
cs.AIcs.NEarXiv:1006.1512v12010

Neural and Evolutionary Computing

A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations

A guide to convolution arithmetic for deep learning

Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video

Transition-Based Dependency Parsing with Stack Long Short-Term Memory

An Implementation of Intrusion Detection System Using Genetic Algorithm

Resnet in Resnet: Generalizing Residual Architectures

A Unified Deep Neural Network for Speaker and Language Recognition

Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition?

Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Going Deeper in Facial Expression Recognition using Deep Neural Networks

Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices

Structured Pruning of Deep Convolutional Neural Networks

Deep convolutional neural networks for predominant instrument recognition in polyphonic music

An Introduction to Convolutional Neural Networks

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks

Listen, Attend and Spell

Towards Deep Neural Network Architectures Robust to Adversarial Examples

Visual7W: Grounded Question Answering in Images

Deep-Plant: Plant Identification with convolutional neural networks

Learning to Compare Image Patches via Convolutional Neural Networks

A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification

Memory and information processing in neuromorphic systems

Unsupervised Learning of Video Representations using LSTMs

Rotation-invariant convolutional neural networks for galaxy morphology prediction

Do Convnets Learn Correspondence?

Transferring Rich Feature Hierarchies for Robust Visual Tracking

The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems

Learning both Weights and Connections for Efficient Neural Networks

Flattened Convolutional Neural Networks for Feedforward Acceleration

Inverting Visual Representations with Convolutional Networks

Stacked What-Where Auto-encoders

How transferable are features in deep neural networks?

Striving for Simplicity: The All Convolutional Net

Spatio-Temporal Backpropagation for Training High-performance Spiking Neural Networks

One weird trick for parallelizing convolutional neural networks

Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images

Long Short-Term Memory Based Recurrent Neural Network Architectures for Large Vocabulary Speech Recognition

graph2vec: Learning Distributed Representations of Graphs

Deep Fried Convnets

A Clockwork RNN

Bidirectional Recurrent Neural Networks for Medical Event Detection in Electronic Health Records

Cuckoo Search: Recent Advances and Applications

Caffe: Convolutional Architecture for Fast Feature Embedding

Learning Longer Memory in Recurrent Neural Networks

Qualitatively characterizing neural network optimization problems

Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks

CMA-ES for Hyperparameter Optimization of Deep Neural Networks

A comprehensive review of firefly algorithms

When Face Recognition Meets with Deep Learning: an Evaluation of Convolutional Neural Networks for Face Recognition

Dropout improves Recurrent Neural Networks for Handwriting Recognition

Image Super-Resolution Using Deep Convolutional Networks

Spectral Networks and Locally Connected Networks on Graphs

Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition

Fast Training of Convolutional Networks through FFTs

Predicting Parameters in Deep Learning

Sequence Transduction with Recurrent Neural Networks

Convolutional Neural Networks Applied to House Numbers Digit Classification

The Deterministic Dendritic Cell Algorithm