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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1,201 to 1,260 of 1,353

SEGAN: Speech Enhancement Generative Adversarial Network
Santiago Pascual, Antonio Bonafonte, Joan Serrà
cs.LGcs.NEcs.SDarXiv:1703.09452v32017
Hamiltonian Neural Networks
Sam Greydanus, Misko Dzamba, Jason Yosinski
cs.NEarXiv:1906.01563v32019
Overcoming catastrophic forgetting with hard attention to the task
Joan Serrà, Dídac Surís, Marius Miron +1
cs.LGcs.AIcs.NEarXiv:1801.01423v32018
Object Detectors Emerge in Deep Scene CNNs
Bolei Zhou, Aditya Khosla, Agata Lapedriza +2
cs.CVcs.NEarXiv:1412.6856v22014
Reinforcement Learning with Unsupervised Auxiliary Tasks
Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki +4
cs.LGcs.NEarXiv:1611.05397v12016
Deep Biaffine Attention for Neural Dependency Parsing
Timothy Dozat, Christopher D. Manning
cs.CLcs.NEarXiv:1611.01734v32016
Convolutional Neural Network Architectures for Matching Natural Language Sentences
Baotian Hu, Zhengdong Lu, Hang Li +1
cs.CLcs.LGcs.NEarXiv:1503.03244v12015
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs
Martin Simonovsky, Nikos Komodakis
cs.CVcs.LGcs.NEarXiv:1704.02901v32017
Towards Accurate Generative Models of Video: A New Metric & Challenges
Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach +3
cs.CVcs.AIcs.LGarXiv:1812.01717v22018
Taskonomy: Disentangling Task Transfer Learning
Amir Zamir, Alexander Sax, William Shen +3
cs.CVcs.AIcs.LGarXiv:1804.08328v12018
How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation
Chia-Wei Liu, Ryan Lowe, Iulian V. Serban +3
cs.CLcs.AIcs.LGarXiv:1603.08023v22016
Predicting Parameters in Deep Learning
Misha Denil, Babak Shakibi, Laurent Dinh +2
cs.LGcs.NEstat.MLarXiv:1306.0543v22013
Spatio-Temporal Backpropagation for Training High-performance Spiking Neural Networks
Yujie Wu, Lei Deng, Guoqi Li +2
cs.NEq-bio.NCstat.MLarXiv:1706.02609v32017
Deep Learning in Spiking Neural Networks
Amirhossein Tavanaei, Masoud Ghodrati, Saeed Reza Kheradpisheh +2
cs.NEcs.AIarXiv:1804.08150v42018
One weird trick for parallelizing convolutional neural networks
Alex Krizhevsky
cs.NEcs.DCcs.LGarXiv:1404.5997v22014
On the Number of Linear Regions of Deep Neural Networks
Guido Montúfar, Razvan Pascanu, Kyunghyun Cho +1
stat.MLcs.LGcs.NEarXiv:1402.1869v22014
Semi-Supervised Learning with Ladder Networks
Antti Rasmus, Harri Valpola, Mikko Honkala +2
cs.NEcs.LGstat.MLarXiv:1507.02672v22015
Sequence-Level Knowledge Distillation
Yoon Kim, Alexander M. Rush
cs.CLcs.LGcs.NEarXiv:1606.07947v42016
Deep clustering: Discriminative embeddings for segmentation and separation
John R. Hershey, Zhuo Chen, Jonathan Le Roux +1
cs.NEcs.LGstat.MLarXiv:1508.04306v12015
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
Loic Landrieu, Martin Simonovsky
cs.CVcs.LGcs.NEarXiv:1711.09869v22017
Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification
Justin Salamon, Juan Pablo Bello
cs.SDcs.CVcs.LGarXiv:1608.04363v22016
Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches
Jure Žbontar, Yann LeCun
cs.CVcs.LGcs.NEarXiv:1510.05970v22015
Learning to Compare Image Patches via Convolutional Neural Networks
Sergey Zagoruyko, Nikos Komodakis
cs.CVcs.LGcs.NEarXiv:1504.03641v12015
Darwin Family: MRI-Trust-Weighted Evolutionary Merging for Training-Free Scaling of Language-Model Reasoning
Taebong Kim, Youngsik Hong, Minsik Kim +4
cs.NEcs.AIarXiv:2605.14386v12026
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models
Wojciech Samek, Thomas Wiegand, Klaus-Robert Müller
cs.AIcs.CYcs.NEarXiv:1708.08296v12017
End-to-End Learning of Geometry and Context for Deep Stereo Regression
Alex Kendall, Hayk Martirosyan, Saumitro Dasgupta +4
cs.CVcs.NEarXiv:1703.04309v12017
Error bounds for approximations with deep ReLU networks
Dmitry Yarotsky
cs.LGcs.NEarXiv:1610.01145v32016
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models
Wieland Brendel, Jonas Rauber, Matthias Bethge
stat.MLcs.CRcs.CVarXiv:1712.04248v22017
RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism
Edward Choi, Mohammad Taha Bahadori, Joshua A. Kulas +3
cs.LGcs.AIcs.NEarXiv:1608.05745v42016
PCANet: A Simple Deep Learning Baseline for Image Classification?
Tsung-Han Chan, Kui Jia, Shenghua Gao +3
cs.CVcs.LGcs.NEarXiv:1404.3606v22014
BranchyNet: Fast Inference via Early Exiting from Deep Neural Networks
Surat Teerapittayanon, Bradley McDanel, H. T. Kung
cs.NEcs.CVcs.LGarXiv:1709.01686v12017
Incorporating Copying Mechanism in Sequence-to-Sequence Learning
Jiatao Gu, Zhengdong Lu, Hang Li +1
cs.CLcs.AIcs.LGarXiv:1603.06393v32016
Growing a Neural Network in Breadth, Depth, and Time
Eivinas Butkus, Kedar Garzón Gupta, Nikolaus Kriegeskorte
q-bio.NCcs.LGcs.NEarXiv:2605.25174v12026
A Convergence Theory for Deep Learning via Over-Parameterization
Zeyuan Allen-Zhu, Yuanzhi Li, Zhao Song
cs.LGcs.DScs.NEarXiv:1811.03962v52018
Deep Convolutional Networks on Graph-Structured Data
Mikael Henaff, Joan Bruna, Yann LeCun
cs.LGcs.CVcs.NEarXiv:1506.05163v12015
An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
Ian J. Goodfellow, Mehdi Mirza, Da Xiao +2
stat.MLcs.LGcs.NEarXiv:1312.6211v32013
Photonics for artificial intelligence and neuromorphic computing
Bhavin J. Shastri, Alexander N. Tait, Thomas Ferreira de Lima +4
physics.opticscs.NEphysics.app-pharXiv:2011.00111v22020
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin, Regina Barzilay, Tommi Jaakkola
cs.LGcs.NEstat.MLarXiv:1802.04364v42018
A guide to convolution arithmetic for deep learning
Vincent Dumoulin, Francesco Visin
stat.MLcs.LGcs.NEarXiv:1603.07285v22016
Character-Aware Neural Language Models
Yoon Kim, Yacine Jernite, David Sontag +1
cs.CLcs.NEstat.MLarXiv:1508.06615v42015
How Does Batch Normalization Help Optimization?
Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas +1
stat.MLcs.LGcs.NEarXiv:1805.11604v52018
Teaching Machines to Read and Comprehend
Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette +4
cs.CLcs.AIcs.NEarXiv:1506.03340v32015
Large-Scale Evolution of Image Classifiers
Esteban Real, Sherry Moore, Andrew Selle +5
cs.NEcs.AIcs.CVarXiv:1703.01041v22017
Training Very Deep Networks
Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber
cs.LGcs.NEarXiv:1507.06228v22015
Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models
Iulian V. Serban, Alessandro Sordoni, Yoshua Bengio +2
cs.CLcs.AIcs.LGarXiv:1507.04808v32015
Evolution Strategies as a Scalable Alternative to Reinforcement Learning
Tim Salimans, Jonathan Ho, Xi Chen +2
stat.MLcs.AIcs.LGarXiv:1703.03864v22017
DeepSurv: Personalized Treatment Recommender System Using A Cox Proportional Hazards Deep Neural Network
Jared Katzman, Uri Shaham, Jonathan Bates +3
stat.MLcs.NEarXiv:1606.00931v32016
Learning from Simulated and Unsupervised Images through Adversarial Training
Ashish Shrivastava, Tomas Pfister, Oncel Tuzel +3
cs.CVcs.LGcs.NEarXiv:1612.07828v22016
Highway Networks
Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber
cs.LGcs.NEarXiv:1505.00387v22015
Understanding Neural Networks Through Deep Visualization
Jason Yosinski, Jeff Clune, Anh Nguyen +2
cs.CVcs.LGcs.NEarXiv:1506.06579v12015
Named Entity Recognition with Bidirectional LSTM-CNNs
Jason P. C. Chiu, Eric Nichols
cs.CLcs.LGcs.NEarXiv:1511.08308v52015
cuDNN: Efficient Primitives for Deep Learning
Sharan Chetlur, Cliff Woolley, Philippe Vandermersch +4
cs.NEcs.LGcs.MSarXiv:1410.0759v32014
Stacked Attention Networks for Image Question Answering
Zichao Yang, Xiaodong He, Jianfeng Gao +2
cs.LGcs.CLcs.CVarXiv:1511.02274v22015
DRAW: A Recurrent Neural Network For Image Generation
Karol Gregor, Ivo Danihelka, Alex Graves +2
cs.CVcs.LGcs.NEarXiv:1502.04623v22015
Alias-Free Generative Adversarial Networks
Tero Karras, Miika Aittala, Samuli Laine +4
cs.CVcs.AIcs.LGarXiv:2106.12423v42021
Summaries:한국어
Return of Frustratingly Easy Domain Adaptation
Baochen Sun, Jiashi Feng, Kate Saenko
cs.CVcs.AIcs.LGarXiv:1511.05547v22015
Sequence Transduction with Recurrent Neural Networks
Alex Graves
cs.NEcs.LGstat.MLarXiv:1211.3711v12012
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
Tim Salimans, Diederik P. Kingma
cs.LGcs.AIcs.NEarXiv:1602.07868v32016
GLU Variants Improve Transformer
Noam Shazeer
cs.LGcs.NEstat.MLarXiv:2002.05202v12020
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
Andrew M. Saxe, James L. McClelland, Surya Ganguli
cs.NEcond-mat.dis-nncs.CVarXiv:1312.6120v32013

Neural and Evolutionary Computing

SEGAN: Speech Enhancement Generative Adversarial Network

Hamiltonian Neural Networks

Overcoming catastrophic forgetting with hard attention to the task

Object Detectors Emerge in Deep Scene CNNs

Reinforcement Learning with Unsupervised Auxiliary Tasks

Deep Biaffine Attention for Neural Dependency Parsing

Convolutional Neural Network Architectures for Matching Natural Language Sentences

Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs

Towards Accurate Generative Models of Video: A New Metric & Challenges

Taskonomy: Disentangling Task Transfer Learning

How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation

Predicting Parameters in Deep Learning

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

Deep Learning in Spiking Neural Networks

One weird trick for parallelizing convolutional neural networks

On the Number of Linear Regions of Deep Neural Networks

Semi-Supervised Learning with Ladder Networks

Sequence-Level Knowledge Distillation

Deep clustering: Discriminative embeddings for segmentation and separation

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification

Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches

Learning to Compare Image Patches via Convolutional Neural Networks

Darwin Family: MRI-Trust-Weighted Evolutionary Merging for Training-Free Scaling of Language-Model Reasoning

Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models

End-to-End Learning of Geometry and Context for Deep Stereo Regression

Error bounds for approximations with deep ReLU networks

Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models

RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism

PCANet: A Simple Deep Learning Baseline for Image Classification?

BranchyNet: Fast Inference via Early Exiting from Deep Neural Networks

Incorporating Copying Mechanism in Sequence-to-Sequence Learning

Growing a Neural Network in Breadth, Depth, and Time

A Convergence Theory for Deep Learning via Over-Parameterization

Deep Convolutional Networks on Graph-Structured Data

An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks

Photonics for artificial intelligence and neuromorphic computing

Junction Tree Variational Autoencoder for Molecular Graph Generation

A guide to convolution arithmetic for deep learning

Character-Aware Neural Language Models

How Does Batch Normalization Help Optimization?

Teaching Machines to Read and Comprehend

Large-Scale Evolution of Image Classifiers

Training Very Deep Networks

Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

DeepSurv: Personalized Treatment Recommender System Using A Cox Proportional Hazards Deep Neural Network

Learning from Simulated and Unsupervised Images through Adversarial Training

Highway Networks

Understanding Neural Networks Through Deep Visualization

Named Entity Recognition with Bidirectional LSTM-CNNs

cuDNN: Efficient Primitives for Deep Learning

Stacked Attention Networks for Image Question Answering

DRAW: A Recurrent Neural Network For Image Generation

Alias-Free Generative Adversarial Networks

Return of Frustratingly Easy Domain Adaptation

Sequence Transduction with Recurrent Neural Networks

Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks

GLU Variants Improve Transformer

Exact solutions to the nonlinear dynamics of learning in deep linear neural networks