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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1,021 to 1,080 of 1,354

Deep Learning is Robust to Massive Label Noise
David Rolnick, Andreas Veit, Serge Belongie +1
cs.LGcs.AIcs.CVarXiv:1705.10694v32017
Deep Reinforcement Learning in Large Discrete Action Spaces
Gabriel Dulac-Arnold, Richard Evans, Hado van Hasselt +7
cs.AIcs.LGcs.NEarXiv:1512.07679v22015
Learning What and Where to Draw
Scott Reed, Zeynep Akata, Santosh Mohan +3
cs.CVcs.NEarXiv:1610.02454v12016
Implicit Regularization in Deep Matrix Factorization
Sanjeev Arora, Nadav Cohen, Wei Hu +1
cs.LGcs.AIcs.NEarXiv:1905.13655v32019
Stochastic Configuration Networks: Fundamentals and Algorithms
Dianhui Wang, Ming Li
cs.NEarXiv:1702.03180v42017
Unsupervised Scalable Representation Learning for Multivariate Time Series
Jean-Yves Franceschi, Aymeric Dieuleveut, Martin Jaggi
cs.LGcs.NEstat.MLarXiv:1901.10738v42019
Why does deep and cheap learning work so well?
Henry W. Lin, Max Tegmark, David Rolnick
cond-mat.dis-nncs.LGcs.NEarXiv:1608.08225v42016
Stochastic Variance Reduction for Nonconvex Optimization
Sashank J. Reddi, Ahmed Hefny, Suvrit Sra +2
math.OCcs.LGcs.NEarXiv:1603.06160v22016
Automated Curriculum Learning for Neural Networks
Alex Graves, Marc G. Bellemare, Jacob Menick +2
cs.NEarXiv:1704.03003v12017
Parameterized Complexity of $L_p$-Lipschitz Constants for Input Convex Neural Networks and $L_p$-Norm Maximization over Zonotopes
Aritra Das, Vincent Froese, Moritz Grillo +6
cs.CCcs.DMcs.LGarXiv:2608.24865v12026
Single State Update Predictive Coding training for Time Series Forecasting and Anomaly Detection
Matteo Cardoni, Sam Leroux
cs.LGcs.NEarXiv:2608.24697v12026
Fast Training of Convolutional Networks through FFTs
Michael Mathieu, Mikael Henaff, Yann LeCun
cs.CVcs.LGcs.NEarXiv:1312.5851v52013
Evolving Deep Convolutional Neural Networks for Image Classification
Yanan Sun, Bing Xue, Mengjie Zhang +1
cs.NEcs.CVarXiv:1710.10741v32017
Analysis Methods in Neural Language Processing: A Survey
Yonatan Belinkov, James Glass
cs.CLcs.LGcs.NEarXiv:1812.08951v22018
Deep Voice: Real-time Neural Text-to-Speech
Sercan O. Arik, Mike Chrzanowski, Adam Coates +9
cs.CLcs.LGcs.NEarXiv:1702.07825v22017
Learning with Pseudo-Ensembles
Philip Bachman, Ouais Alsharif, Doina Precup
stat.MLcs.LGcs.NEarXiv:1412.4864v12014
Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison
Dongxu Li, Cristian Rodriguez Opazo, Xin Yu +1
cs.CVcs.HCcs.MMarXiv:1910.11006v22019
Two-Archive Evolutionary Algorithm for Constrained Multi-Objective Optimization
Ke Li, Renzhi Chen, Guangtao Fu +1
cs.NEarXiv:1711.07907v12017
A Brief Review of Nature-Inspired Algorithms for Optimization
Iztok Fister, Xin-She Yang, Iztok Fister +2
cs.NEarXiv:1307.4186v12013
ORBITALIF: An Efficient Spiking Federated Learning Framework for Onboard Cloud Removal
Bohan Zhang, Chenyu Xu, Yijie Mao +1
cs.NEcs.AIcs.CVarXiv:2608.24073v12026
Detecting and Correcting for Label Shift with Black Box Predictors
Zachary C. Lipton, Yu-Xiang Wang, Alex Smola
cs.LGcs.AIcs.NEarXiv:1802.03916v32018
ParEVO: Synthesizing Code for Irregular Data: High-Performance Parallelism through Agentic Evolution
Liu Yang, Zeyu Nie, Andrew Liu +4
cs.LGcs.DCcs.NEarXiv:2603.02510v22026
Multimodal Deep Learning for Robust RGB-D Object Recognition
Andreas Eitel, Jost Tobias Springenberg, Luciano Spinello +2
cs.CVcs.LGcs.NEarXiv:1507.06821v22015
Norm-Based Capacity Control in Neural Networks
Behnam Neyshabur, Ryota Tomioka, Nathan Srebro
cs.LGcs.AIcs.NEarXiv:1503.00036v22015
Parameter Space Noise for Exploration
Matthias Plappert, Rein Houthooft, Prafulla Dhariwal +6
cs.LGcs.AIcs.NEarXiv:1706.01905v22017
Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches
Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach
cs.IRcs.LGcs.NEarXiv:1907.06902v32019
Summaries:한국어
COMIC: Agentic Sketch Comedy Generation
Susung Hong, Brian Curless, Ira Kemelmacher-Shlizerman +1
cs.CVcs.AIcs.CLarXiv:2603.11048v12026
Value Iteration Networks
Aviv Tamar, Yi Wu, Garrett Thomas +2
cs.AIcs.LGcs.NEarXiv:1602.02867v42016
SuperSpike: Supervised learning in multi-layer spiking neural networks
Friedemann Zenke, Surya Ganguli
q-bio.NCcs.LGcs.NEarXiv:1705.11146v22017
Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection
Xiaojun Xu, Chang Liu, Qian Feng +3
cs.CRcs.NEarXiv:1708.06525v42017
DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data Processing
Shuochao Yao, Shaohan Hu, Yiran Zhao +2
cs.LGcs.NEcs.NIarXiv:1611.01942v22016
Searching for Activation Functions
Prajit Ramachandran, Barret Zoph, Quoc V. Le
cs.NEcs.CVcs.LGarXiv:1710.05941v22017
Hopfield Networks is All You Need
Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner +13
cs.NEcs.CLcs.LGarXiv:2008.02217v32020
Spicing up Genetic Netlist Generation with LLMs
Stefan Uhlich, Yağız Gençer, Andrea Bonetti +4
cs.NEcs.ARcs.LGarXiv:2608.23317v12026
Rotation-invariant convolutional neural networks for galaxy morphology prediction
Sander Dieleman, Kyle W. Willett, Joni Dambre
astro-ph.IMastro-ph.GAcs.CVarXiv:1503.07077v12015
Automatically designing CNN architectures using genetic algorithm for image classification
Yanan Sun, Bing Xue, Mengjie Zhang +1
cs.NEarXiv:1808.03818v32018
Deep Evidential Regression
Alexander Amini, Wilko Schwarting, Ava Soleimany +1
cs.LGcs.NEstat.MLarXiv:1910.02600v22019
Generating Multi-label Discrete Patient Records using Generative Adversarial Networks
Edward Choi, Siddharth Biswal, Bradley Malin +3
cs.LGcs.NEarXiv:1703.06490v32017
A Probabilistic U-Net for Segmentation of Ambiguous Images
Simon A. A. Kohl, Bernardino Romera-Paredes, Clemens Meyer +6
cs.CVcs.LGcs.NEarXiv:1806.05034v42018
Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders
Nat Dilokthanakul, Pedro A. M. Mediano, Marta Garnelo +4
cs.LGcs.NEstat.MLarXiv:1611.02648v22016
TasNet: time-domain audio separation network for real-time, single-channel speech separation
Yi Luo, Nima Mesgarani
cs.SDcs.LGcs.MMarXiv:1711.00541v22017
Inverting Visual Representations with Convolutional Networks
Alexey Dosovitskiy, Thomas Brox
cs.NEcs.CVcs.LGarXiv:1506.02753v42015
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
Anh Nguyen, Alexey Dosovitskiy, Jason Yosinski +2
cs.NEcs.AIcs.CVarXiv:1605.09304v52016
One-Shot Imitation Learning
Yan Duan, Marcin Andrychowicz, Bradly C. Stadie +5
cs.AIcs.LGcs.NEarXiv:1703.07326v32017
FormuEvo: LLM-Guided Evolution for Discovering Solver-Efficient Mixed-Integer Programming Formulations
Haofeng Yuan, Jianing Peng, Jieyi Bi +3
cs.CLcs.NEarXiv:2608.23353v12026
Going Deeper With Directly-Trained Larger Spiking Neural Networks
Hanle Zheng, Yujie Wu, Lei Deng +2
cs.NEcs.AIarXiv:2011.05280v22020
Mish: A Self Regularized Non-Monotonic Activation Function
Diganta Misra
cs.LGcs.CVcs.NEarXiv:1908.08681v32019
Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity inspired by Network Science
Decebal Constantin Mocanu, Elena Mocanu, Peter Stone +3
cs.NEcs.AIcs.LGarXiv:1707.04780v22017
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Yanbin Liu, Juho Lee, Minseop Park +4
cs.LGcs.CVcs.NEarXiv:1805.10002v52018
Reinforcement Learning from Meta-Evaluation: Aligning Language Models Without Ground-Truth Labels
Micah Rentschler, Jesse Roberts
cs.NEarXiv:2601.21268v12026
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
Felipe Petroski Such, Vashisht Madhavan, Edoardo Conti +3
cs.NEcs.LGarXiv:1712.06567v32017
Memory and information processing in neuromorphic systems
Giacomo Indiveri, Shih-Chii Liu
cs.NEarXiv:1506.03264v12015
Dynamic Memory Networks for Visual and Textual Question Answering
Caiming Xiong, Stephen Merity, Richard Socher
cs.NEcs.CLcs.CVarXiv:1603.01417v12016
A Simple Way to Initialize Recurrent Networks of Rectified Linear Units
Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton
cs.NEcs.LGarXiv:1504.00941v22015
Object detection via a multi-region & semantic segmentation-aware CNN model
Spyros Gidaris, Nikos Komodakis
cs.CVcs.LGcs.NEarXiv:1505.01749v32015
Artificial Immune Systems
Uwe Aickelin, Dipankar Dasgupta
cs.AIcs.NEarXiv:0910.4899v12009
Roulette-wheel selection via stochastic acceptance
Adam Lipowski, Dorota Lipowska
cs.NEcond-mat.stat-mechcs.CCarXiv:1109.3627v22011
Optoelectronic Reservoir Computing
Yvan Paquot, François Duport, Anteo Smerieri +4
cs.ETcs.LGcs.NEarXiv:1111.7219v12011
Reasoning about Entailment with Neural Attention
Tim Rocktäschel, Edward Grefenstette, Karl Moritz Hermann +2
cs.CLcs.AIcs.LGarXiv:1509.06664v42015
Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS
Petro Liashchynskyi, Pavlo Liashchynskyi
cs.LGcs.NEstat.MLarXiv:1912.06059v12019

Neural and Evolutionary Computing

Deep Learning is Robust to Massive Label Noise

Deep Reinforcement Learning in Large Discrete Action Spaces

Learning What and Where to Draw

Implicit Regularization in Deep Matrix Factorization

Stochastic Configuration Networks: Fundamentals and Algorithms

Unsupervised Scalable Representation Learning for Multivariate Time Series

Why does deep and cheap learning work so well?

Stochastic Variance Reduction for Nonconvex Optimization

Automated Curriculum Learning for Neural Networks

Parameterized Complexity of $L_p$-Lipschitz Constants for Input Convex Neural Networks and $L_p$-Norm Maximization over Zonotopes

Single State Update Predictive Coding training for Time Series Forecasting and Anomaly Detection

Fast Training of Convolutional Networks through FFTs

Evolving Deep Convolutional Neural Networks for Image Classification

Analysis Methods in Neural Language Processing: A Survey

Deep Voice: Real-time Neural Text-to-Speech

Learning with Pseudo-Ensembles

Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison

Two-Archive Evolutionary Algorithm for Constrained Multi-Objective Optimization

A Brief Review of Nature-Inspired Algorithms for Optimization

ORBITALIF: An Efficient Spiking Federated Learning Framework for Onboard Cloud Removal

Detecting and Correcting for Label Shift with Black Box Predictors

ParEVO: Synthesizing Code for Irregular Data: High-Performance Parallelism through Agentic Evolution

Multimodal Deep Learning for Robust RGB-D Object Recognition

Norm-Based Capacity Control in Neural Networks

Parameter Space Noise for Exploration

Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches

COMIC: Agentic Sketch Comedy Generation

Value Iteration Networks

SuperSpike: Supervised learning in multi-layer spiking neural networks

Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection

DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data Processing

Searching for Activation Functions

Hopfield Networks is All You Need

Spicing up Genetic Netlist Generation with LLMs

Rotation-invariant convolutional neural networks for galaxy morphology prediction

Automatically designing CNN architectures using genetic algorithm for image classification

Deep Evidential Regression

Generating Multi-label Discrete Patient Records using Generative Adversarial Networks

A Probabilistic U-Net for Segmentation of Ambiguous Images

Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders

TasNet: time-domain audio separation network for real-time, single-channel speech separation

Inverting Visual Representations with Convolutional Networks

Synthesizing the preferred inputs for neurons in neural networks via deep generator networks

One-Shot Imitation Learning

FormuEvo: LLM-Guided Evolution for Discovering Solver-Efficient Mixed-Integer Programming Formulations

Going Deeper With Directly-Trained Larger Spiking Neural Networks

Mish: A Self Regularized Non-Monotonic Activation Function

Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity inspired by Network Science

Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning

Reinforcement Learning from Meta-Evaluation: Aligning Language Models Without Ground-Truth Labels

Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

Memory and information processing in neuromorphic systems

Dynamic Memory Networks for Visual and Textual Question Answering

A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

Object detection via a multi-region & semantic segmentation-aware CNN model

Artificial Immune Systems

Roulette-wheel selection via stochastic acceptance

Optoelectronic Reservoir Computing

Reasoning about Entailment with Neural Attention

Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS