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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61 to 120 of 1,352

GeoTrussRover: Morphological Computation with Contact-Semantic Control Primitives
Muyuan Ma, Yi Zhang, Yang Yang +12
cs.ROcs.GRcs.NEarXiv:2609.11361v12026
Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks
Andrea Soltoggio, Kenneth O. Stanley, Sebastian Risi
cs.NEcs.AIarXiv:1703.10371v32017
Multiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator
Matthew J. Marinella, Sapan Agarwal, Alexander Hsia +6
cs.ARcs.NEarXiv:1707.09952v22017
Generating Long Videos of Dynamic Scenes
Brooks, Tim, Hellsten, Janne, Aittala, Miika +6
cs.CVcs.AIcs.LGarXiv:2206.03429v22022
Dynamic Evaluation of Neural Sequence Models
Ben Krause, Emmanuel Kahembwe, Iain Murray +1
cs.NEcs.CLarXiv:1709.07432v22017
Scale-Invariant Convolutional Neural Networks
Yichong Xu, Tianjun Xiao, Jiaxing Zhang +2
cs.CVcs.LGcs.NEarXiv:1411.6369v12014
Breaking the Central Bias: Spatially Partitioned Experts for Coordinate-Based Neuroevolution
Romain Claret, Arthur Gygax, Michael O'Neill +3
cs.NEcs.CVcs.LGarXiv:2609.11518v12026
Guiding High-Performance SAT Solvers with Unsat-Core Predictions
Daniel Selsam, Nikolaj Bjørner
cs.NEarXiv:1903.04671v72019
Rethinking Differentiable Search for Mixed-Precision Neural Networks
Zhaowei Cai, Nuno Vasconcelos
cs.LGcs.CVcs.NEarXiv:2004.05795v12020
On Extended Long Short-term Memory and Dependent Bidirectional Recurrent Neural Network
Yuanhang Su, C. -C. Jay Kuo
cs.LGcs.CLcs.NEarXiv:1803.01686v52018
Prediction of Compression Index of Fine-Grained Soils Using a Gene Expression Programming Model
Danial Mohammadzadeh, Seyed-Farzan Kazemi, Amir Mosavi +2
stat.APcs.LGcs.NEarXiv:1907.04913v12019
Neuroevolution in Games: State of the Art and Open Challenges
Sebastian Risi, Julian Togelius
cs.NEarXiv:1410.7326v32014
Predicting Privacy Leakage from Weight Spectral Density
Richard J. Preen, Jim Smith
cs.LGcs.CRcs.NEarXiv:2609.11780v12026
Solving Few-Shot Multiobjective Multitask Optimization via Iterative Sequential Transfer
Tingyang Wei, Haofeng Wu, Ananda Phan Iman +3
cs.LGcs.AIcs.NEarXiv:2609.11228v12026
MOEA/D with Angle-based Constrained Dominance Principle for Constrained Multi-objective Optimization Problems
Zhun Fan, Yi Fang, Wenji Li +3
cs.NEarXiv:1802.03608v12018
SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks
Rui-Jie Zhu, Qihang Zhao, Guoqi Li +1
cs.CLcs.LGcs.NEarXiv:2302.13939v52023
Phases in a class of associative memories via hidden neurons
Toshihiro Ota, Masato Taki
cs.LGcond-mat.dis-nncs.NEarXiv:2609.10976v12026
Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models
Jesse Engel, Matthew Hoffman, Adam Roberts
cs.LGcs.NEstat.MLarXiv:1711.05772v22017
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System
Sebastian Schmitt, Johann Klaehn, Guillaume Bellec +22
cs.NEarXiv:1703.01909v12017
Principal Graphs and Manifolds
A. N. Gorban, A. Y. Zinovyev
cs.LGcs.NEstat.MLarXiv:0809.0490v22008
Deep learning is a good steganalysis tool when embedding key is reused for different images, even if there is a cover source-mismatch
Lionel Pibre, Pasquet Jérôme, Dino Ienco +1
cs.MMcs.CVcs.LGarXiv:1511.04855v22015
DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization
Haoran Ye, Jiarui Wang, Zhiguang Cao +2
cs.NEcs.AIcs.LGarXiv:2309.14032v22023
Making Neural Programming Architectures Generalize via Recursion
Jonathon Cai, Richard Shin, Dawn Song
cs.LGcs.NEcs.PLarXiv:1704.06611v12017
Block-Recurrent Transformers
DeLesley Hutchins, Imanol Schlag, Yuhuai Wu +2
cs.LGcs.AIcs.NEarXiv:2203.07852v32022
Benchmarking in Optimization: Best Practice and Open Issues
Thomas Bartz-Beielstein, Carola Doerr, Daan van den Berg +14
cs.NEcs.PFmath.OCarXiv:2007.03488v22020
CMA-ES for Hyperparameter Optimization of Deep Neural Networks
Ilya Loshchilov, Frank Hutter
cs.NEcs.LGarXiv:1604.07269v12016
Towards Bayesian Deep Learning: A Framework and Some Existing Methods
Hao Wang, Dit-Yan Yeung
stat.MLcs.CVcs.LGarXiv:1608.06884v22016
Progressive Tandem Learning for Pattern Recognition with Deep Spiking Neural Networks
Jibin Wu, Chenglin Xu, Daquan Zhou +2
cs.NEarXiv:2007.01204v12020
On the Preliminary Design of Multiple Gravity-Assist Trajectories
Massimiliano Vasile, Paolo DePascale
math.OCcs.NEeess.SYarXiv:1105.1822v12011
Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices
Tayfun Gokmen, O. Murat Onen, Wilfried Haensch
cs.LGcs.NEstat.MLarXiv:1705.08014v12017
GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet
Shan You, Tao Huang, Mingmin Yang +3
cs.CVcs.NEarXiv:2003.11236v12020
Backpropagation-free Training of Deep Physical Neural Networks
Ali Momeni, Babak Rahmani, Matthieu Mallejac +2
cs.LGcs.NEphysics.app-pharXiv:2304.11042v32023
MorphIC: A 65-nm 738k-Synapse/mm$^2$ Quad-Core Binary-Weight Digital Neuromorphic Processor with Stochastic Spike-Driven Online Learning
Charlotte Frenkel, Jean-Didier Legat, David Bol
cs.NEcs.ETarXiv:1904.08513v22019
Building competitive direct acoustics-to-word models for English conversational speech recognition
Kartik Audhkhasi, Brian Kingsbury, Bhuvana Ramabhadran +2
cs.CLcs.AIcs.NEarXiv:1712.03133v12017
AdaBits: Neural Network Quantization with Adaptive Bit-Widths
Qing Jin, Linjie Yang, Zhenyu Liao
cs.CVcs.LGcs.NEarXiv:1912.09666v22019
Optimal Regularization Can Mitigate Double Descent
Preetum Nakkiran, Prayaag Venkat, Sham Kakade +1
cs.LGcs.NEmath.STarXiv:2003.01897v22020
CIF: Continuous Integrate-and-Fire for End-to-End Speech Recognition
Linhao Dong, Bo Xu
cs.CLcs.LGcs.NEarXiv:1905.11235v42019
Fractional Order Load-Frequency Control of Interconnected Power Systems Using Chaotic Multi-objective Optimization
Indranil Pan, Saptarshi Das
math.OCcs.NEeess.SYarXiv:1611.09802v12016
Why should we add early exits to neural networks?
Simone Scardapane, Michele Scarpiniti, Enzo Baccarelli +1
cs.NEcs.LGstat.MLarXiv:2004.12814v22020
Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Chao-Han Huck Yang, Yun-Yun Tsai, Pin-Yu Chen
cs.LGcs.AIcs.NEarXiv:2106.09296v32021
Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?
Sharif Abuadbba, Kyuyeon Kim, Minki Kim +5
cs.CRcs.LGcs.NEarXiv:2003.12365v12020
The phase diagram of approximation rates for deep neural networks
Dmitry Yarotsky, Anton Zhevnerchuk
cs.NEcs.LGarXiv:1906.09477v22019
Structural Fusion of Bayesian Networks with Limited Treewidth Using Genetic Algorithms
Pablo Torrijos, José A. Gámez, José M. Puerta
cs.NEcs.LGarXiv:2609.10276v12026
Compressing Convolutional Neural Networks
Wenlin Chen, James T. Wilson, Stephen Tyree +2
cs.LGcs.CVcs.NEarXiv:1506.04449v12015
Parallel Graph Partitioning for Complex Networks
Henning Meyerhenke, Peter Sanders, Christian Schulz
cs.DCcs.DScs.NEarXiv:1404.4797v32014
FBNETGEN: Task-aware GNN-based fMRI Analysis via Functional Brain Network Generation
Xuan Kan, Hejie Cui, Joshua Lukemire +2
cs.LGcs.NEeess.IVarXiv:2205.12465v22022
Training CNNs with Low-Rank Filters for Efficient Image Classification
Yani Ioannou, Duncan Robertson, Jamie Shotton +2
cs.CVcs.LGcs.NEarXiv:1511.06744v32015
T2FSNN: Deep Spiking Neural Networks with Time-to-first-spike Coding
Seongsik Park, Seijoon Kim, Byunggook Na +1
cs.NEcs.LGstat.MLarXiv:2003.11741v12020
Efficient Dataset Distillation Using Random Feature Approximation
Noel Loo, Ramin Hasani, Alexander Amini +1
cs.LGcs.AIcs.NEarXiv:2210.12067v12022
Analyzing and Mitigating the Impact of Permanent Faults on a Systolic Array Based Neural Network Accelerator
Jeff Zhang, Tianyu Gu, Kanad Basu +1
cs.LGcs.ARcs.CVarXiv:1802.04657v22018
Training Trajectories Determine Circuit Removability in Annealable Soft-Prior Transformers
Zonglin Yang, Ziming Zhao, Wei Tang +5
cs.LGcs.NEarXiv:2609.10287v12026
Event-Based Backpropagation can compute Exact Gradients for Spiking Neural Networks
Timo C. Wunderlich, Christian Pehle
q-bio.NCcs.NEarXiv:2009.08378v32020
Human action recognition with a large-scale brain-inspired photonic computer
Piotr Antonik, Nicolas Marsal, Daniel Brunner +1
cs.NEarXiv:2004.02545v12020
Simulating a perceptron on a quantum computer
Maria Schuld, Ilya Sinayskiy, Francesco Petruccione
quant-phcs.LGcs.NEarXiv:1412.3635v12014
Programming with a Differentiable Forth Interpreter
Matko Bošnjak, Tim Rocktäschel, Jason Naradowsky +1
cs.NEcs.AIcs.LGarXiv:1605.06640v32016
Swapout: Learning an ensemble of deep architectures
Saurabh Singh, Derek Hoiem, David Forsyth
cs.CVcs.LGcs.NEarXiv:1605.06465v12016
Robust Industrial Cyber Physical Classification Using Neuromorphic Temporal Embeddings and Hybrid SNN XGBoost Under Machine Unlearning Attacks
Ammar Kamoona, Sajad Koushkbaghi, Mahdi Jalili +2
cs.LGcs.CRcs.NEarXiv:2609.09564v12026
Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions
Rui Wang, Joel Lehman, Aditya Rawal +4
cs.NEarXiv:2003.08536v22020
Evolving embodied intelligence from materials to machines
David Howard, Agoston E. Eiben, Danielle Frances Kennedy +3
cs.ROcond-mat.mtrl-scics.LGarXiv:1901.05704v12019
Convolutional LSTM Networks for Subcellular Localization of Proteins
Søren Kaae Sønderby, Casper Kaae Sønderby, Henrik Nielsen +1
q-bio.QMcs.NEarXiv:1503.01919v12015

Neural and Evolutionary Computing

GeoTrussRover: Morphological Computation with Contact-Semantic Control Primitives

Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks

Multiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator

Generating Long Videos of Dynamic Scenes

Dynamic Evaluation of Neural Sequence Models

Scale-Invariant Convolutional Neural Networks

Breaking the Central Bias: Spatially Partitioned Experts for Coordinate-Based Neuroevolution

Guiding High-Performance SAT Solvers with Unsat-Core Predictions

Rethinking Differentiable Search for Mixed-Precision Neural Networks

On Extended Long Short-term Memory and Dependent Bidirectional Recurrent Neural Network

Prediction of Compression Index of Fine-Grained Soils Using a Gene Expression Programming Model

Neuroevolution in Games: State of the Art and Open Challenges

Predicting Privacy Leakage from Weight Spectral Density

Solving Few-Shot Multiobjective Multitask Optimization via Iterative Sequential Transfer

MOEA/D with Angle-based Constrained Dominance Principle for Constrained Multi-objective Optimization Problems

SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Phases in a class of associative memories via hidden neurons

Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models

Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System

Principal Graphs and Manifolds

Deep learning is a good steganalysis tool when embedding key is reused for different images, even if there is a cover source-mismatch

DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization

Making Neural Programming Architectures Generalize via Recursion

Block-Recurrent Transformers

Benchmarking in Optimization: Best Practice and Open Issues

CMA-ES for Hyperparameter Optimization of Deep Neural Networks

Towards Bayesian Deep Learning: A Framework and Some Existing Methods

Progressive Tandem Learning for Pattern Recognition with Deep Spiking Neural Networks

On the Preliminary Design of Multiple Gravity-Assist Trajectories

Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices

GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet

Backpropagation-free Training of Deep Physical Neural Networks

MorphIC: A 65-nm 738k-Synapse/mm$^2$ Quad-Core Binary-Weight Digital Neuromorphic Processor with Stochastic Spike-Driven Online Learning

Building competitive direct acoustics-to-word models for English conversational speech recognition

AdaBits: Neural Network Quantization with Adaptive Bit-Widths

Optimal Regularization Can Mitigate Double Descent

CIF: Continuous Integrate-and-Fire for End-to-End Speech Recognition

Fractional Order Load-Frequency Control of Interconnected Power Systems Using Chaotic Multi-objective Optimization

Why should we add early exits to neural networks?

Voice2Series: Reprogramming Acoustic Models for Time Series Classification

Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?

The phase diagram of approximation rates for deep neural networks

Structural Fusion of Bayesian Networks with Limited Treewidth Using Genetic Algorithms

Compressing Convolutional Neural Networks

Parallel Graph Partitioning for Complex Networks

FBNETGEN: Task-aware GNN-based fMRI Analysis via Functional Brain Network Generation

Training CNNs with Low-Rank Filters for Efficient Image Classification

T2FSNN: Deep Spiking Neural Networks with Time-to-first-spike Coding

Efficient Dataset Distillation Using Random Feature Approximation

Analyzing and Mitigating the Impact of Permanent Faults on a Systolic Array Based Neural Network Accelerator

Training Trajectories Determine Circuit Removability in Annealable Soft-Prior Transformers

Event-Based Backpropagation can compute Exact Gradients for Spiking Neural Networks

Human action recognition with a large-scale brain-inspired photonic computer

Simulating a perceptron on a quantum computer

Programming with a Differentiable Forth Interpreter

Swapout: Learning an ensemble of deep architectures

Robust Industrial Cyber Physical Classification Using Neuromorphic Temporal Embeddings and Hybrid SNN XGBoost Under Machine Unlearning Attacks

Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions

Evolving embodied intelligence from materials to machines

Convolutional LSTM Networks for Subcellular Localization of Proteins