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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1,081 to 1,140 of 1,353

Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks
Wei Fang, Zhaofei Yu, Yanqi Chen +3
cs.NEcs.CVcs.LGarXiv:2007.05785v52020
Neuromorphic Silicon Photonic Networks
Alexander N. Tait, Thomas Ferreira de Lima, Ellen Zhou +4
q-bio.NCcs.NEphysics.opticsarXiv:1611.02272v32016
Delving Deeper into Convolutional Networks for Learning Video Representations
Nicolas Ballas, Li Yao, Chris Pal +1
cs.CVcs.LGcs.NEarXiv:1511.06432v42015
Structured Pruning of Deep Convolutional Neural Networks
Sajid Anwar, Kyuyeon Hwang, Wonyong Sung
cs.NEcs.LGstat.MLarXiv:1512.08571v12015
Adaptive Computation Time for Recurrent Neural Networks
Alex Graves
cs.NEarXiv:1603.08983v62016
Human Pose Estimation with Iterative Error Feedback
Joao Carreira, Pulkit Agrawal, Katerina Fragkiadaki +1
cs.CVcs.LGcs.NEarXiv:1507.06550v32015
Linear Mode Connectivity and the Lottery Ticket Hypothesis
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy +1
cs.LGcs.NEstat.MLarXiv:1912.05671v42019
Deep Residual Learning in Spiking Neural Networks
Wei Fang, Zhaofei Yu, Yanqi Chen +3
cs.NEarXiv:2102.04159v62021
Transition-Based Dependency Parsing with Stack Long Short-Term Memory
Chris Dyer, Miguel Ballesteros, Wang Ling +2
cs.CLcs.LGcs.NEarXiv:1505.08075v12015
PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks
Jian Tang, Meng Qu, Qiaozhu Mei
cs.CLcs.LGcs.NEarXiv:1508.00200v12015
Variable Rate Image Compression with Recurrent Neural Networks
George Toderici, Sean M. O'Malley, Sung Jin Hwang +5
cs.CVcs.LGcs.NEarXiv:1511.06085v52015
Spiking Neural Networks for Continuous Control: Neuromorphic Reinforcement Learning in Conventional Computing
Jessica Hunter, Md Maruf Hossain Shuvo, Krishna Roy
cs.LGcs.NEarXiv:2608.22729v12026
Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark
Timo Hackel, Nikolay Savinov, Lubor Ladicky +3
cs.CVcs.LGcs.NEarXiv:1704.03847v12017
Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition
Charles F. Cadieu, Ha Hong, Daniel L. K. Yamins +5
q-bio.NCcs.NEarXiv:1406.3284v12014
Model compression via distillation and quantization
Antonio Polino, Razvan Pascanu, Dan Alistarh
cs.NEcs.LGarXiv:1802.05668v12018
Accelerating Very Deep Convolutional Networks for Classification and Detection
Xiangyu Zhang, Jianhua Zou, Kaiming He +1
cs.CVcs.LGcs.NEarXiv:1505.06798v22015
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition
Ehsan Kharazmi, Zhongqiang Zhang, George Em Karniadakis
cs.NEcs.LGmath.NAarXiv:2003.05385v12020
Revisiting Distributed Synchronous SGD
Jianmin Chen, Xinghao Pan, Rajat Monga +2
cs.LGcs.DCcs.NEarXiv:1604.00981v32016
Fast Transformer Decoding: One Write-Head is All You Need
Noam Shazeer
cs.NEcs.CLcs.LGarXiv:1911.02150v12019
Adversarially Robust Generalization Requires More Data
Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras +2
cs.LGcs.NEstat.MLarXiv:1804.11285v22018
A Neural Representation of Sketch Drawings
David Ha, Douglas Eck
cs.NEcs.LGstat.MLarXiv:1704.03477v42017
Nature-Inspired Optimization Algorithms: Challenges and Open Problems
Xin-She Yang
cs.NEcs.LGmath.OCarXiv:2003.03776v12020
graph2vec: Learning Distributed Representations of Graphs
Annamalai Narayanan, Mahinthan Chandramohan, Rajasekar Venkatesan +3
cs.AIcs.CLcs.CRarXiv:1707.05005v12017
Neural Style Transfer: A Review
Yongcheng Jing, Yezhou Yang, Zunlei Feng +3
cs.CVcs.NEeess.IVarXiv:1705.04058v72017
ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks
Xiaohan Ding, Yuchen Guo, Guiguang Ding +1
cs.CVcs.LGcs.NEarXiv:1908.03930v32019
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar, Peyton Greenside, Anna Shcherbina +1
cs.LGcs.CVcs.NEarXiv:1605.01713v32016
Self-labelling via simultaneous clustering and representation learning
Yuki Markus Asano, Christian Rupprecht, Andrea Vedaldi
cs.CVcs.NEarXiv:1911.05371v32019
Rationalizing Neural Predictions
Tao Lei, Regina Barzilay, Tommi Jaakkola
cs.CLcs.NEarXiv:1606.04155v22016
Enhanced Artificial Neural Networks Using QHAdamW in Air Quality Forecasting
Mary Joy Daniel Vinas
cs.AIcs.ETcs.LGarXiv:2608.21463v12026
PDE-Net: Learning PDEs from Data
Zichao Long, Yiping Lu, Xianzhong Ma +1
math.NAcs.LGcs.NEarXiv:1710.09668v22017
Towards Deep Neural Network Architectures Robust to Adversarial Examples
Shixiang Gu, Luca Rigazio
cs.LGcs.CVcs.NEarXiv:1412.5068v42014
Overcoming Exploration in Reinforcement Learning with Demonstrations
Ashvin Nair, Bob McGrew, Marcin Andrychowicz +2
cs.LGcs.AIcs.NEarXiv:1709.10089v22017
Gated Feedback Recurrent Neural Networks
Junyoung Chung, Caglar Gulcehre, Kyunghyun Cho +1
cs.NEcs.LGstat.MLarXiv:1502.02367v42015
EvolVE: Evolutionary Search for LLM-based Verilog Generation and Optimization
Wei-Po Hsin, Ren-Hao Deng, Yao-Ting Hsieh +2
cs.AIcs.NEcs.PLarXiv:2601.18067v12026
Neural NILM: Deep Neural Networks Applied to Energy Disaggregation
Jack Kelly, William Knottenbelt
cs.NEarXiv:1507.06594v32015
Learned Primal-dual Reconstruction
Jonas Adler, Ozan Öktem
math.OCcs.CVcs.NEarXiv:1707.06474v32017
A Neural Network Approach to Context-Sensitive Generation of Conversational Responses
Alessandro Sordoni, Michel Galley, Michael Auli +6
cs.CLcs.AIcs.LGarXiv:1506.06714v12015
Understanding LSTM -- a tutorial into Long Short-Term Memory Recurrent Neural Networks
Ralf C. Staudemeyer, Eric Rothstein Morris
cs.NEcs.CLcs.LGarXiv:1909.09586v12019
Population Based Training of Neural Networks
Max Jaderberg, Valentin Dalibard, Simon Osindero +9
cs.LGcs.NEarXiv:1711.09846v22017
Unitary Evolution Recurrent Neural Networks
Martin Arjovsky, Amar Shah, Yoshua Bengio
cs.LGcs.NEstat.MLarXiv:1511.06464v42015
Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
Albert Gatt, Emiel Krahmer
cs.CLcs.AIcs.NEarXiv:1703.09902v42017
Training Spiking Neural Networks Using Lessons From Deep Learning
Jason K. Eshraghian, Max Ward, Emre Neftci +6
cs.NEcs.ETcs.LGarXiv:2109.12894v62021
Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces
Alice Coucke, Alaa Saade, Adrien Ball +9
cs.CLcs.NEarXiv:1805.10190v32018
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare
Yiqiang Chen, Jindong Wang, Chaohui Yu +2
cs.LGcs.AIcs.NEarXiv:1907.09173v22019
Controlled Self-Evolution for Algorithmic Code Optimization
Tu Hu, Ronghao Chen, Shuo Zhang +9
cs.CLcs.AIcs.NEarXiv:2601.07348v52026
Deep Convolutional Inverse Graphics Network
Tejas D. Kulkarni, Will Whitney, Pushmeet Kohli +1
cs.CVcs.GRcs.LGarXiv:1503.03167v42015
Imaging Time-Series to Improve Classification and Imputation
Zhiguang Wang, Tim Oates
cs.LGcs.NEstat.MLarXiv:1506.00327v12015
Hierarchical Representations for Efficient Architecture Search
Hanxiao Liu, Karen Simonyan, Oriol Vinyals +2
cs.LGcs.CVcs.NEarXiv:1711.00436v22017
Evolving Deep Neural Networks
Risto Miikkulainen, Jason Liang, Elliot Meyerson +8
cs.NEcs.AIarXiv:1703.00548v22017
PathNet: Evolution Channels Gradient Descent in Super Neural Networks
Chrisantha Fernando, Dylan Banarse, Charles Blundell +5
cs.NEcs.LGarXiv:1701.08734v12017
Going Deeper in Facial Expression Recognition using Deep Neural Networks
Ali Mollahosseini, David Chan, Mohammad H. Mahoor
cs.NEcs.CVarXiv:1511.04110v12015
Network Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures
Hengyuan Hu, Rui Peng, Yu-Wing Tai +1
cs.NEcs.CVcs.LGarXiv:1607.03250v12016
Fast Algorithms for Convolutional Neural Networks
Andrew Lavin, Scott Gray
cs.NEcs.LGarXiv:1509.09308v22015
Unity: A General Platform for Intelligent Agents
Arthur Juliani, Vincent-Pierre Berges, Ervin Teng +8
cs.LGcs.AIcs.NEarXiv:1809.02627v22018
MADE: Masked Autoencoder for Distribution Estimation
Mathieu Germain, Karol Gregor, Iain Murray +1
cs.LGcs.NEstat.MLarXiv:1502.03509v22015
"Zero-Shot" Super-Resolution using Deep Internal Learning
Assaf Shocher, Nadav Cohen, Michal Irani
cs.CVcs.LGcs.NEarXiv:1712.06087v12017
Illuminating search spaces by mapping elites
Jean-Baptiste Mouret, Jeff Clune
cs.AIcs.NEcs.ROarXiv:1504.04909v12015
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
Torsten Hoefler, Dan Alistarh, Tal Ben-Nun +2
cs.LGcs.AIcs.ARarXiv:2102.00554v12021
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
William Lotter, Gabriel Kreiman, David Cox
cs.LGcs.AIcs.CVarXiv:1605.08104v52016
Visual7W: Grounded Question Answering in Images
Yuke Zhu, Oliver Groth, Michael Bernstein +1
cs.CVcs.LGcs.NEarXiv:1511.03416v42015

Neural and Evolutionary Computing

Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks

Neuromorphic Silicon Photonic Networks

Delving Deeper into Convolutional Networks for Learning Video Representations

Structured Pruning of Deep Convolutional Neural Networks

Adaptive Computation Time for Recurrent Neural Networks

Human Pose Estimation with Iterative Error Feedback

Linear Mode Connectivity and the Lottery Ticket Hypothesis

Deep Residual Learning in Spiking Neural Networks

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

PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks

Variable Rate Image Compression with Recurrent Neural Networks

Spiking Neural Networks for Continuous Control: Neuromorphic Reinforcement Learning in Conventional Computing

Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark

Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition

Model compression via distillation and quantization

Accelerating Very Deep Convolutional Networks for Classification and Detection

hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition

Revisiting Distributed Synchronous SGD

Fast Transformer Decoding: One Write-Head is All You Need

Adversarially Robust Generalization Requires More Data

A Neural Representation of Sketch Drawings

Nature-Inspired Optimization Algorithms: Challenges and Open Problems

graph2vec: Learning Distributed Representations of Graphs

Neural Style Transfer: A Review

ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks

Not Just a Black Box: Learning Important Features Through Propagating Activation Differences

Self-labelling via simultaneous clustering and representation learning

Rationalizing Neural Predictions

Enhanced Artificial Neural Networks Using QHAdamW in Air Quality Forecasting

PDE-Net: Learning PDEs from Data

Towards Deep Neural Network Architectures Robust to Adversarial Examples

Overcoming Exploration in Reinforcement Learning with Demonstrations

Gated Feedback Recurrent Neural Networks

EvolVE: Evolutionary Search for LLM-based Verilog Generation and Optimization

Neural NILM: Deep Neural Networks Applied to Energy Disaggregation

Learned Primal-dual Reconstruction

A Neural Network Approach to Context-Sensitive Generation of Conversational Responses

Understanding LSTM -- a tutorial into Long Short-Term Memory Recurrent Neural Networks

Population Based Training of Neural Networks

Unitary Evolution Recurrent Neural Networks

Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

Training Spiking Neural Networks Using Lessons From Deep Learning

Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces

FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare

Controlled Self-Evolution for Algorithmic Code Optimization

Deep Convolutional Inverse Graphics Network

Imaging Time-Series to Improve Classification and Imputation

Hierarchical Representations for Efficient Architecture Search

Evolving Deep Neural Networks

PathNet: Evolution Channels Gradient Descent in Super Neural Networks

Going Deeper in Facial Expression Recognition using Deep Neural Networks

Network Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures

Fast Algorithms for Convolutional Neural Networks

Unity: A General Platform for Intelligent Agents

MADE: Masked Autoencoder for Distribution Estimation

"Zero-Shot" Super-Resolution using Deep Internal Learning

Illuminating search spaces by mapping elites

Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks

Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning

Visual7W: Grounded Question Answering in Images