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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1,801 to 1,835 of 1,835

Towards Explainable Artificial Intelligence
Wojciech Samek, Klaus-Robert Müller
cs.AIcs.LGcs.NEarXiv:1909.12072v12019
Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Future
Grace W. Lindsay
q-bio.NCcs.CVcs.NEarXiv:2001.07092v22020
Learning Features by Watching Objects Move
Deepak Pathak, Ross Girshick, Piotr Dollár +2
cs.CVcs.AIcs.LGarXiv:1612.06370v22016
Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks
Martin Engelcke, Dushyant Rao, Dominic Zeng Wang +2
cs.ROcs.AIcs.CVarXiv:1609.06666v22016
Summaries:한국어
NiftyNet: a deep-learning platform for medical imaging
Eli Gibson, Wenqi Li, Carole Sudre +14
cs.CVcs.LGcs.NEarXiv:1709.03485v22017
Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks
Hardik Sharma, Jongse Park, Naveen Suda +5
cs.NEcs.ARarXiv:1712.01507v22017
A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations
Holger R. Roth, Le Lu, Ari Seff +6
cs.CVcs.LGcs.NEarXiv:1406.2639v12014
AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery
Izhar Wallach, Michael Dzamba, Abraham Heifets
cs.LGcs.NEq-bio.BMarXiv:1510.02855v12015
Ansor: Generating High-Performance Tensor Programs for Deep Learning
Lianmin Zheng, Chengfan Jia, Minmin Sun +9
cs.LGcs.NEcs.PFarXiv:2006.06762v52020
Deep learning for neuroimaging: a validation study
Sergey M. Plis, Devon R. Hjelm, Ruslan Salakhutdinov +1
cs.NEcs.LGstat.MLarXiv:1312.5847v32013
Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science
Randal S. Olson, Nathan Bartley, Ryan J. Urbanowicz +1
cs.NEcs.AIcs.LGarXiv:1603.06212v12016
Deep Learning is Robust to Massive Label Noise
David Rolnick, Andreas Veit, Serge Belongie +1
cs.LGcs.AIcs.CVarXiv:1705.10694v32017
Searching for Activation Functions
Prajit Ramachandran, Barret Zoph, Quoc V. Le
cs.NEcs.CVcs.LGarXiv:1710.05941v22017
Deep Evidential Regression
Alexander Amini, Wilko Schwarting, Ava Soleimany +1
cs.LGcs.NEstat.MLarXiv:1910.02600v22019
Mish: A Self Regularized Non-Monotonic Activation Function
Diganta Misra
cs.LGcs.CVcs.NEarXiv:1908.08681v32019
A Simple Way to Initialize Recurrent Networks of Rectified Linear Units
Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton
cs.NEcs.LGarXiv:1504.00941v22015
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
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
Deep Convolutional Inverse Graphics Network
Tejas D. Kulkarni, Will Whitney, Pushmeet Kohli +1
cs.CVcs.GRcs.LGarXiv:1503.03167v42015
PACEvolve: Enabling Long-Horizon Progress-Aware Consistent Evolution
Minghao Yan, Bo Peng, Benjamin Coleman +13
cs.NEcs.LGarXiv:2601.10657v22026
Universal statistical signatures of evolution in artificial intelligence architectures
Theodor Spiro
q-bio.PEcs.AIcs.CYarXiv:2604.10571v12026
Fine-Grain GPU Parallelization of the Generalized Partition Crossover for Large-Scale Traveling Salesman Problems
Swetha Varadarajan, Darrell Whitley
cs.AIcs.NEarXiv:2608.21233v12026
Virtual Worlds as Proxy for Multi-Object Tracking Analysis
Adrien Gaidon, Qiao Wang, Yohann Cabon +1
cs.CVcs.LGcs.NEarXiv:1605.06457v12016
CNN-RNN: A Unified Framework for Multi-label Image Classification
Jiang Wang, Yi Yang, Junhua Mao +3
cs.CVcs.LGcs.NEarXiv:1604.04573v12016
Taskonomy: Disentangling Task Transfer Learning
Amir Zamir, Alexander Sax, William Shen +3
cs.CVcs.AIcs.LGarXiv:1804.08328v12018
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
BranchyNet: Fast Inference via Early Exiting from Deep Neural Networks
Surat Teerapittayanon, Bradley McDanel, H. T. Kung
cs.NEcs.CVcs.LGarXiv:1709.01686v12017
Gate-Variants of Gated Recurrent Unit (GRU) Neural Networks
Rahul Dey, Fathi M. Salem
cs.NEstat.MLarXiv:1701.05923v12017
Learning to learn by gradient descent by gradient descent
Marcin Andrychowicz, Misha Denil, Sergio Gomez +5
cs.NEcs.LGarXiv:1606.04474v22016
A Structured Self-attentive Sentence Embedding
Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos +4
cs.CLcs.AIcs.LGarXiv:1703.03130v12017
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David
cs.LGcs.CVcs.NEarXiv:1511.00363v32015
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
Convolutional Neural Networks for Sentence Classification
Yoon Kim
cs.CLcs.NEarXiv:1408.5882v22014

Neural and Evolutionary Computing

Towards Explainable Artificial Intelligence

Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Future

Learning Features by Watching Objects Move

Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks

NiftyNet: a deep-learning platform for medical imaging

Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks

A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations

AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery

Ansor: Generating High-Performance Tensor Programs for Deep Learning

Deep learning for neuroimaging: a validation study

Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science

Deep Learning is Robust to Massive Label Noise

Searching for Activation Functions

Deep Evidential Regression

Mish: A Self Regularized Non-Monotonic Activation Function

A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

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

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

Deep Convolutional Inverse Graphics Network

PACEvolve: Enabling Long-Horizon Progress-Aware Consistent Evolution

Universal statistical signatures of evolution in artificial intelligence architectures

Fine-Grain GPU Parallelization of the Generalized Partition Crossover for Large-Scale Traveling Salesman Problems

Virtual Worlds as Proxy for Multi-Object Tracking Analysis

CNN-RNN: A Unified Framework for Multi-label Image Classification

Taskonomy: Disentangling Task Transfer Learning

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification

BranchyNet: Fast Inference via Early Exiting from Deep Neural Networks

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

Learning to learn by gradient descent by gradient descent

A Structured Self-attentive Sentence Embedding

BinaryConnect: Training Deep Neural Networks with binary weights during propagations

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

The Mythos of Model Interpretability

Convolutional Neural Networks for Sentence Classification