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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1,261 to 1,320 of 1,353

Gate-Variants of Gated Recurrent Unit (GRU) Neural Networks
Rahul Dey, Fathi M. Salem
cs.NEstat.MLarXiv:1701.05923v12017
Flower Pollination Algorithm for Global Optimization
Xin-She Yang
math.OCcs.NEnlin.AOarXiv:1312.5673v12013
Learning to learn by gradient descent by gradient descent
Marcin Andrychowicz, Misha Denil, Sergio Gomez +5
cs.NEcs.LGarXiv:1606.04474v22016
Deep Speech: Scaling up end-to-end speech recognition
Awni Hannun, Carl Case, Jared Casper +8
cs.CLcs.LGcs.NEarXiv:1412.5567v22014
DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients
Shuchang Zhou, Yuxin Wu, Zekun Ni +3
cs.NEcs.LGarXiv:1606.06160v32016
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
Tianqi Chen, Mu Li, Yutian Li +7
cs.DCcs.LGcs.MSarXiv:1512.01274v12015
A Structured Self-attentive Sentence Embedding
Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos +4
cs.CLcs.AIcs.LGarXiv:1703.03130v12017
All-Optical Machine Learning Using Diffractive Deep Neural Networks
Xing Lin, Yair Rivenson, Nezih T. Yardimci +3
cs.NEcs.LGphysics.comp-pharXiv:1804.08711v22018
Learning Structured Sparsity in Deep Neural Networks
Wei Wen, Chunpeng Wu, Yandan Wang +2
cs.NEcs.LGstat.MLarXiv:1608.03665v42016
Listen, Attend and Spell
William Chan, Navdeep Jaitly, Quoc V. Le +1
cs.CLcs.LGcs.NEarXiv:1508.01211v22015
Deeply-Supervised Nets
Chen-Yu Lee, Saining Xie, Patrick Gallagher +2
stat.MLcs.CVcs.LGarXiv:1409.5185v22014
Recurrent Neural Networks for Multivariate Time Series with Missing Values
Zhengping Che, Sanjay Purushotham, Kyunghyun Cho +2
cs.LGcs.NEstat.MLarXiv:1606.01865v22016
Neural Turing Machines
Alex Graves, Greg Wayne, Ivo Danihelka
cs.NEarXiv:1410.5401v22014
Hierarchical Graph Representation Learning with Differentiable Pooling
Rex Ying, Jiaxuan You, Christopher Morris +3
cs.LGcs.NEcs.SIarXiv:1806.08804v42018
Unsupervised Learning of Video Representations using LSTMs
Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov
cs.LGcs.CVcs.NEarXiv:1502.04681v32015
A Critical Review of Recurrent Neural Networks for Sequence Learning
Zachary C. Lipton, John Berkowitz, Charles Elkan
cs.LGcs.NEarXiv:1506.00019v42015
Deep Networks with Stochastic Depth
Gao Huang, Yu Sun, Zhuang Liu +2
cs.LGcs.CVcs.NEarXiv:1603.09382v32016
Decoupled Weight Decay Regularization
Ilya Loshchilov, Frank Hutter
cs.LGcs.NEmath.OCarXiv:1711.05101v32017
Attention-Based Models for Speech Recognition
Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk +2
cs.CLcs.LGcs.NEarXiv:1506.07503v12015
Hindsight Experience Replay
Marcin Andrychowicz, Filip Wolski, Alex Ray +7
cs.LGcs.AIcs.NEarXiv:1707.01495v32017
Pixel Recurrent Neural Networks
Aaron van den Oord, Nal Kalchbrenner, Koray Kavukcuoglu
cs.CVcs.LGcs.NEarXiv:1601.06759v32016
Temporal Ensembling for Semi-Supervised Learning
Samuli Laine, Timo Aila
cs.NEcs.LGarXiv:1610.02242v32016
MatConvNet - Convolutional Neural Networks for MATLAB
Andrea Vedaldi, Karel Lenc
cs.CVcs.LGcs.MSarXiv:1412.4564v32014
Recurrent Neural Network Regularization
Wojciech Zaremba, Ilya Sutskever, Oriol Vinyals
cs.NEarXiv:1409.2329v52014
Efficient Neural Architecture Search via Parameter Sharing
Hieu Pham, Melody Y. Guan, Barret Zoph +2
cs.LGcs.CLcs.CVarXiv:1802.03268v22018
Cyclical Learning Rates for Training Neural Networks
Leslie N. Smith
cs.CVcs.LGcs.NEarXiv:1506.01186v62015
Session-based Recommendations with Recurrent Neural Networks
Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas +1
cs.LGcs.IRcs.NEarXiv:1511.06939v42015
Deep learning with convolutional neural networks for EEG decoding and visualization
Robin Tibor Schirrmeister, Jost Tobias Springenberg, Lukas Dominique Josef Fiederer +6
cs.LGcs.NEarXiv:1703.05051v52017
DarwinX: Evolving Agent Harnesses Through Natural Selection
Yifan Zhang, Yutong Dai, Juntao Tan +9
cs.NEcs.AIcs.LGarXiv:2608.07545v12026
The Role of Grid Cells in Reducing Spatial Aliasing in Hippocampal Place Representations
Alexander Johnson, Obadah Ghizawi, Ali A. Minai
cs.NEcs.AIcs.ROarXiv:2608.18569v12026
Striving for Simplicity: The All Convolutional Net
Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox +1
cs.LGcs.CVcs.NEarXiv:1412.6806v32014
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn, Pieter Abbeel, Sergey Levine
cs.LGcs.AIcs.CVarXiv:1703.03400v32017
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Nguyen, Jason Yosinski, Jeff Clune
cs.CVcs.AIcs.NEarXiv:1412.1897v42014
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David
cs.LGcs.CVcs.NEarXiv:1511.00363v32015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
Nicolas Papernot, Patrick McDaniel, Xi Wu +2
cs.CRcs.LGcs.NEarXiv:1511.04508v22015
Regularized Evolution for Image Classifier Architecture Search
Esteban Real, Alok Aggarwal, Yanping Huang +1
cs.NEcs.AIcs.CVarXiv:1802.01548v72018
Generative Adversarial Text to Image Synthesis
Scott Reed, Zeynep Akata, Xinchen Yan +3
cs.NEcs.CVarXiv:1605.05396v22016
Pointer Networks
Oriol Vinyals, Meire Fortunato, Navdeep Jaitly
stat.MLcs.CGcs.LGarXiv:1506.03134v22015
Convolutional Networks on Graphs for Learning Molecular Fingerprints
David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre +4
cs.LGcs.NEstat.MLarXiv:1509.09292v22015
In Defense of the Triplet Loss for Person Re-Identification
Alexander Hermans, Lucas Beyer, Bastian Leibe
cs.CVcs.NEarXiv:1703.07737v42017
Deep CORAL: Correlation Alignment for Deep Domain Adaptation
Baochen Sun, Kate Saenko
cs.CVcs.AIcs.LGarXiv:1607.01719v12016
An Introduction to Convolutional Neural Networks
Keiron O'Shea, Ryan Nash
cs.NEcs.CVcs.LGarXiv:1511.08458v22015
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Jonathan Frankle, Michael Carbin
cs.LGcs.AIcs.NEarXiv:1803.03635v52018
Generating Sequences With Recurrent Neural Networks
Alex Graves
cs.NEcs.CLarXiv:1308.0850v52013
Graphical Design of Interpretable Architectures
Pietro Barbiero
cs.LGcs.AIcs.NEarXiv:2608.18936v12026
Density estimation using Real NVP
Laurent Dinh, Jascha Sohl-Dickstein, Samy Bengio
cs.LGcs.AIcs.NEarXiv:1605.08803v32016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Dan Hendrycks, Kevin Gimpel
cs.NEcs.CVcs.LGarXiv:1610.02136v32016
The Mythos of Model Interpretability
Zachary C. Lipton
cs.LGcs.AIcs.CVarXiv:1606.03490v32016
End to End Learning for Self-Driving Cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski +10
cs.CVcs.LGcs.NEarXiv:1604.07316v12016
A New Metaheuristic Bat-Inspired Algorithm
Xin-She Yang
math.OCcs.NEphysics.bio-pharXiv:1004.4170v12010
FitNets: Hints for Thin Deep Nets
Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou +3
cs.LGcs.NEarXiv:1412.6550v42014
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar, Peyton Greenside, Anshul Kundaje
cs.CVcs.LGcs.NEarXiv:1704.02685v22017
SeisEvo: Evolution of Seismic Data Reconstruction Algorithms by Agents
Yingjie Xu, Siwei Yu, Jianwei Ma
physics.geo-phcs.AIcs.NEarXiv:2608.18272v12026
Low-Power, Neuromorphic, Acoustic Anomaly Detection for Persistent Machine Monitoring
Steven C. Nesbit, Victor M. Vergara, Michael A. Felix +4
cs.NEcs.AIcs.ETarXiv:2608.18341v12026
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos +2
cs.CVcs.LGcs.NEarXiv:1412.7062v42014
In-Datacenter Performance Analysis of a Tensor Processing Unit
Norman P. Jouppi, Cliff Young, Nishant Patil +72
cs.ARcs.LGcs.NEarXiv:1704.04760v12017
Spectral Networks and Locally Connected Networks on Graphs
Joan Bruna, Wojciech Zaremba, Arthur Szlam +1
cs.LGcs.CVcs.NEarXiv:1312.6203v32013
Recent Advances in Convolutional Neural Networks
Jiuxiang Gu, Zhenhua Wang, Jason Kuen +9
cs.CVcs.LGcs.NEarXiv:1512.07108v62015
Neural Architecture Search with Reinforcement Learning
Barret Zoph, Quoc V. Le
cs.LGcs.AIcs.NEarXiv:1611.01578v22016
Network In Network
Min Lin, Qiang Chen, Shuicheng Yan
cs.NEcs.CVcs.LGarXiv:1312.4400v32013

Neural and Evolutionary Computing

Gate-Variants of Gated Recurrent Unit (GRU) Neural Networks

Flower Pollination Algorithm for Global Optimization

Learning to learn by gradient descent by gradient descent

Deep Speech: Scaling up end-to-end speech recognition

DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

A Structured Self-attentive Sentence Embedding

All-Optical Machine Learning Using Diffractive Deep Neural Networks

Learning Structured Sparsity in Deep Neural Networks

Listen, Attend and Spell

Deeply-Supervised Nets

Recurrent Neural Networks for Multivariate Time Series with Missing Values

Neural Turing Machines

Hierarchical Graph Representation Learning with Differentiable Pooling

Unsupervised Learning of Video Representations using LSTMs

A Critical Review of Recurrent Neural Networks for Sequence Learning

Deep Networks with Stochastic Depth

Decoupled Weight Decay Regularization

Attention-Based Models for Speech Recognition

Hindsight Experience Replay

Pixel Recurrent Neural Networks

Temporal Ensembling for Semi-Supervised Learning

MatConvNet - Convolutional Neural Networks for MATLAB

Recurrent Neural Network Regularization

Efficient Neural Architecture Search via Parameter Sharing

Cyclical Learning Rates for Training Neural Networks

Session-based Recommendations with Recurrent Neural Networks

Deep learning with convolutional neural networks for EEG decoding and visualization

DarwinX: Evolving Agent Harnesses Through Natural Selection

The Role of Grid Cells in Reducing Spatial Aliasing in Hippocampal Place Representations

Striving for Simplicity: The All Convolutional Net

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

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

BinaryConnect: Training Deep Neural Networks with binary weights during propagations

Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks

Regularized Evolution for Image Classifier Architecture Search

Generative Adversarial Text to Image Synthesis

Pointer Networks

Convolutional Networks on Graphs for Learning Molecular Fingerprints

In Defense of the Triplet Loss for Person Re-Identification

Deep CORAL: Correlation Alignment for Deep Domain Adaptation

An Introduction to Convolutional Neural Networks

The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Generating Sequences With Recurrent Neural Networks

Graphical Design of Interpretable Architectures

Density estimation using Real NVP

A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

The Mythos of Model Interpretability

End to End Learning for Self-Driving Cars

A New Metaheuristic Bat-Inspired Algorithm

FitNets: Hints for Thin Deep Nets

Learning Important Features Through Propagating Activation Differences

SeisEvo: Evolution of Seismic Data Reconstruction Algorithms by Agents

Low-Power, Neuromorphic, Acoustic Anomaly Detection for Persistent Machine Monitoring

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

In-Datacenter Performance Analysis of a Tensor Processing Unit

Spectral Networks and Locally Connected Networks on Graphs

Recent Advances in Convolutional Neural Networks

Neural Architecture Search with Reinforcement Learning

Network In Network