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ORCIDNeural Computation, Volume 31
Volume 31, Number 1, January 2019
- Gunnar Blohm, Paul Schrater, Konrad P. Körding
:
Ten Simple Rules for Organizing and Running a Successful Intensive Two-Week Course. - Terry Elliott:
First Passage Time Memory Lifetimes for Simple, Multistate Synapses: Beyond the Eigenvector Requirement. - Erik Rybakken, Nils A. Baas, Benjamin A. Dunn:
Decoding of Neural Data Using Cohomological Feature Extraction. - Carina Curto, Jesse Geneson, Katherine Morrison:
Fixed Points of Competitive Threshold-Linear Networks. - Tianci Liu, Zelin Shi, Yunpeng Liu:
Supervised Dimensionality Reduction on Grassmannian for Image Set Recognition. - Hugo C. C. Carneiro, Carlos Eduardo Pedreira, Felipe M. G. França, Priscila M. V. Lima:
The Exact VC Dimension of the WiSARD n-Tuple Classifier. - Haibin Li, Yangtian Li, Shangjie Li:
Dual Neural Network Method for Solving Multiple Definite Integrals.
Volume 31, Number 2, February 2019
- Christophe Gardella, Olivier Marre, Thierry Mora:
Modeling the Correlated Activity of Neural Populations: A Review. - Michael J. Berry II, Felix Lebois, Avi Ziskind, Rava Azeredo da Silveira:
Functional Diversity in the Retina Improves the Population Code. - Benjamin Scellier, Yoshua Bengio:
Equivalence of Equilibrium Propagation and Recurrent Backpropagation. - Conor J. Houghton:
Calculating the Mutual Information between Two Spike Trains. - W. Shane Grant, Laurent Itti:
Learning Invariant Features in Modulatory Networks through Conflict and Ambiguity. - Jeffrey E. Arle, Nicolae Iftimia, Jay L. Shils, Longzhi Mei, Kristen W. Carlson:
Dynamic Computational Model of the Human Spinal Cord Connectome. - Andersen Man Shun Ang, Nicolas Gillis:
Accelerating Nonnegative Matrix Factorization Algorithms Using Extrapolation. - Sebastian Gottwald, Daniel A. Braun:
Systems of Bounded Rational Agents with Information-Theoretic Constraints.
Volume 31, Number 3, March 2019
- Peter L. Bartlett, David P. Helmbold, Philip M. Long:
Gradient Descent with Identity Initialization Efficiently Learns Positive-Definite Linear Transformations by Deep Residual Networks. - Enzo Marinari:
Forgetting Memories and Their Attractiveness. - Haojie Hu, Rong Wang, Xiaojun Yang, Feiping Nie:
Scalable and Flexible Unsupervised Feature Selection. - Michael Hauser, Sean Gunn, Samer Saab Jr., Asok Ray:
State-Space Representations of Deep Neural Networks. - Anh Tuan Nguyen, Jian Xu, Diu Khue Luu, Qi Zhao, Zhi Yang:
Advancing System Performance with Redundancy: From Biological to Artificial Designs. - Seyed Mohammad Ali Rahmati, Mostafa Rostami, Alireza Karimi:
A Novel Optimization Framework to Improve the Computational Cost of Muscle Activation Prediction for a Neuromusculoskeletal System. - DJ Strouse, David J. Schwab:
The Information Bottleneck and Geometric Clustering.
Volume 31, Number 4, April 2019
- Diego A. Mesa, Justin Tantiongloc, Marcela Mendoza, Sanggyun Kim, Todd P. Coleman:
A Distributed Framework for the Construction of Transport Maps. - Matteo di Volo, Alberto Romagnoni, Cristiano Capone, Alain Destexhe:
Biologically Realistic Mean-Field Models of Conductance-Based Networks of Spiking Neurons with Adaptation. - Zoran Tiganj, Samuel J. Gershman, Per B. Sederberg, Marc W. Howard:
Estimating Scale-Invariant Future in Continuous Time. - Daniel R. Kepple, Hamza Giaffar, Dmitry Rinberg, Alexei A. Koulakov:
Deconstructing Odorant Identity via Primacy in Dual Networks. - Frédéric Crevecoeur, Michel Gevers:
Filtering Compensation for Delays and Prediction Errors during Sensorimotor Control. - Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio:
Gated Orthogonal Recurrent Units: On Learning to Forget. - Yohei Saito, Takuya Kato:
Decreasing the Size of the Restricted Boltzmann Machine. - Gonzalo Safont, Addisson Salazar, Luis Vergara:
Multiclass Alpha Integration of Scores from Multiple Classifiers.
Volume 31, Number 5, May 2019
- Shun-ichi Amari, Ryo Karakida, Masafumi Oizumi, Marco Cuturi:
Information Geometry for Regularized Optimal Transport and Barycenters of Patterns. 827-848 - Jan Gosmann, Chris Eliasmith:
Vector-Derived Transformation Binding: An Improved Binding Operation for Deep Symbol-Like Processing in Neural Networks. 849-869 - Thomas Bose, Andreagiovanni Reina, James A. R. Marshall:
Inhibition and Excitation Shape Activity Selection: Effect of Oscillations in a Decision-Making Circuit. 870-896 - Roman Vyskovský, Daniel Schwarz, Tomás Kaspárek:
Brain Morphometry Methods for Feature Extraction in Random Subspace Ensemble Neural Network Classification of First-Episode Schizophrenia. 897-918 - Xianlun Tang, Wei-Chang Ma, De-Song Kong, Wei Li:
Semisupervised Deep Stacking Network with Adaptive Learning Rate Strategy for Motor Imagery EEG Recognition. 919-942 - Peng Yi, ShiNung Ching:
Multiple Timescale Online Learning Rules for Information Maximization with Energetic Constraints. 943-979 - Purushottam D. Dixit:
Introducing User-Prescribed Constraints in Markov Chains for Nonlinear Dimensionality Reduction. 980-997 - Heiko Hoffmann:
Sparse Associative Memory. 998-1014
Volume 31, Number 6, June 2019
- John A. Berkowitz, Tatyana O. Sharpee:
Quantifying Information Conveyed by Large Neuronal Populations. 1015-1047 - Vafa Andalibi, Henri Hokkanen, Simo Vanni:
Controlling Complexity of Cerebral Cortex Simulations - I: CxSystem, a Flexible Cortical Simulation Framework. 1048-1065 - Henri Hokkanen, Vafa Andalibi, Simo Vanni:
Controlling Complexity of Cerebral Cortex Simulations - II: Streamlined Microcircuits. 1066-1084 - Po-He Tseng, Núria Armengol Urpi, Mikhail Lebedev, Miguel A. L. Nicolelis:
Decoding Movements from Cortical Ensemble Activity Using a Long Short-Term Memory Recurrent Network. 1085-1113 - Mina A. Khoei, Sio-Hoi Ieng, Ryad Benosman:
Asynchronous Event-Based Motion Processing: From Visual Events to Probabilistic Sensory Representation. 1114-1138 - Francesca Mastrogiuseppe, Srdjan Ostojic:
A Geometrical Analysis of Global Stability in Trained Feedback Networks. 1139-1182 - Suwa Xu, Bochao Jia, Faming Liang:
Learning Moral Graphs in Construction of High-Dimensional Bayesian Networks for Mixed Data. 1183-1214 - Yunhua Chen, Yingchao Mai, Jinsheng Xiao, Ling Zhang:
Improving the Antinoise Ability of DNNs via a Bio-Inspired Noise Adaptive Activation Function Rand Softplus. 1215-1233
Volume 31, Number 7, July 2019
- Yong Yu, Xiaosheng Si, Changhua Hu, Jianxun Zhang:
A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures. 1235-1270 - Anup Das, Daniel Sexton, Claudia Lainscsek, Sydney S. Cash, Terrence J. Sejnowski:
Characterizing Brain Connectivity From Human Electrocorticography Recordings With Unobserved Inputs During Epileptic Seizures. 1271-1326 - Kunling Geng, Dae C. Shin, Dong Song, Robert E. Hampson, Samuel A. Deadwyler, Theodore W. Berger, Vasilis Z. Marmarelis:
Multi-Input, Multi-Output Neuronal Mode Network Approach to Modeling the Encoding Dynamics and Functional Connectivity of Neural Systems. 1327-1355 - Guanghao Sun, Shaomin Zhang, Yajie Zhang, Kai Xu, Qiaosheng Zhang, Ting Zhao, Xiaoxiang Zheng:
Effective Dimensionality Reduction for Visualizing Neural Dynamics by Laplacian Eigenmaps. 1356-1379 - Nima Dehghani, Ralf D. Wimmer:
A Computational Perspective of the Role of the Thalamus in Cognition. 1380-1418 - Lennart Gustafsson:
A Case of Near-Optimal Sensory Integration Based on Kohonen Self-Organizing Maps. 1419-1429 - Ryan Pyle, Robert Rosenbaum:
A Reservoir Computing Model of Reward-Modulated Motor Learning and Automaticity. 1430-1461 - Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling:
Effect of Depth and Width on Local Minima in Deep Learning. 1462-1498 - Amandeep Singh Bhatia, Mandeep Kaur Saggi, Ajay Kumar, Sushma Jain:
Matrix Product State-Based Quantum Classifier. 1499-1517
Volume 31, Number 8, August 2019
- David M. Schwartz, Onur Ozan Koyluoglu:
On the Organization of Grid and Place Cells: Neural Denoising via Subspace Learning. 1519-1550 - Bryan P. Tripp:
Approximating the Architecture of Visual Cortex in a Convolutional Network. 1551-1591 - Nicola Bulso, Matteo Marsili, Yasser Roudi:
On the Complexity of Logistic Regression Models. 1592-1623 - David J. Miller, Yujia Wang, George Kesidis:
When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN Classifiers at Test Time. 1624-1670 - Jérôme Tubiana, Simona Cocco, Rémi Monasson:
Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins. 1671-1717 - Kota Matsui, Wataru Kumagai, Kenta Kanamori, Mitsuaki Nishikimi, Takafumi Kanamori:
Variable Selection for Nonparametric Learning with Power Series Kernels. 1718-1750
Volume 31, Number 9, September 2019
- Ali Yousefi, Ishita Basu, Angelique C. Paulk, Noam Peled, Emad N. Eskandar, Darin D. Dougherty, Sydney S. Cash, Alik S. Widge, Uri T. Eden:
Decoding Hidden Cognitive States From Behavior and Physiology Using a Bayesian Approach. 1751-1788 - Teun van Gils, Paul H. E. Tiesinga, Bernhard Englitz, Marijn B. Martens:
Sensitivity to Stimulus Irregularity Is Inherent in Neural Networks. 1789-1824 - Dorian Florescu, Daniel Coca:
Learning with Precise Spike Times: A New Decoding Algorithm for Liquid State Machines. 1825-1852 - S. M. Heidarieh, Mehran Jahed, Ali Ghazizadeh:
A New Nonlinear Sparse Component Analysis for a Biologically Plausible Model of Neurons. 1853-1873 - Encarni Marcos, Fabrizio Londei, Aldo Genovesio:
Hidden Markov Models Predict the Future Choice Better Than a PSTH-Based Method. 1874-1890 - Hirokazu Kameoka, Li Li, Shota Inoue, Shoji Makino:
Supervised Determined Source Separation with Multichannel Variational Autoencoder. 1891-1914
Volume 31, Number 10, October 2019
- Jagadish Bandaru, Pradeep Kumar Mishra, Pavana Ravi Sai Kiran Malyala, Pachamuthu Rajalakshmi:
A Real-Time Health 4.0 Framework with Novel Feature Extraction and Classification for Brain-Controlled IoT-Enabled Environments. 1915-1944 - Brian A. Mitchell, Nina Lauharatanahirun, Javier O. Garcia, Nicholas F. Wymbs, Scott T. Grafton, Jean M. Vettel, Linda R. Petzold:
A Minimum Free Energy Model of Motor Learning. 1945-1963 - Yuxiu Shao, Binxu Wang, Andrew T. Sornborger, Louis Tao:
A Mechanism for Synaptic Copy Between Neural Circuits. 1964-1984 - Chen Beer, Omri Barak:
One Step Back, Two Steps Forward: Interference and Learning in Recurrent Neural Networks. 1985-2003 - Alexander J. A. Ty, Zheng Fang, Rivver A. Gonzalez, Paul J. Rozdeba, Henry D. I. Abarbanel:
Machine Learning of Time Series Using Time-Delay Embedding and Precision Annealing. 2004-2024
Volume 31, Number 11, November 2019
- Ahmadreza Ahmadi, Jun Tani:
A Novel Predictive-Coding-Inspired Variational RNN Model for Online Prediction and Recognition. 2025-2074 - Roozbeh Farhoodi, Khashayar Filom, Ilenna Simone Jones, Konrad P. Körding:
On Functions Computed on Trees. 2075-2137 - Luis Gonzalo Sánchez Giraldo, Odelia Schwartz:
Integrating Flexible Normalization into Midlevel Representations of Deep Convolutional Neural Networks. 2138-2176 - Saurabh Bhaskar Shaw, Kiret Dhindsa, James P. Reilly, Suzanna Becker:
Capturing the Forest but Missing the Trees: Microstates Inadequate for Characterizing Shorter-Scale EEG Dynamics. 2177-2211 - Terry Elliott:
Dynamic Integrative Synaptic Plasticity Explains the Spacing Effect in the Transition from Short- to Long-Term Memory. 2212-2251 - Felix Weissenberger, Marcelo Matheus Gauy, Xun Zou, Angelika Steger:
Mutual Inhibition with Few Inhibitory Cells via Nonlinear Inhibitory Synaptic Interaction. 2252-2265 - Xin Yao, Tianchi Huang, Chenglei Wu, Rui-Xiao Zhang, Lifeng Sun:
Adversarial Feature Alignment: Avoid Catastrophic Forgetting in Incremental Task Lifelong Learning. 2266-2291
Volume 31, Number 12, December 2019
- Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling:
Every Local Minimum Value Is the Global Minimum Value of Induced Model in Nonconvex Machine Learning. 2293-2323 - Davide Spalla, Alexis M. Dubreuil, Sophie Rosay, Rémi Monasson, Alessandro Treves:
Can Grid Cell Ensembles Represent Multiple Spaces? 2324-2347 - Tian Han, Xianglei Xing, Jiawen Wu, Ying Nian Wu:
Replicating Neuroscience Observations on ML/MF and AM Face Patches by Deep Generative Model. 2348-2367 - Mengwen Yuan, Xi Wu, Rui Yan, Huajin Tang:
Reinforcement Learning in Spiking Neural Networks with Stochastic and Deterministic Synapses. 2368-2389 - Takuya Isomura, Thomas Parr, Karl J. Friston:
Bayesian Filtering with Multiple Internal Models: Toward a Theory of Social Intelligence. 2390-2431 - Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama:
Safe Triplet Screening for Distance Metric Learning. 2432-2491 - Gabriel A. Silva:
The Effect of Signaling Latencies and Node Refractory States on the Dynamics of Networks. 2492-2522 - Lili Su, Chia-Jung Chang, Nancy A. Lynch:
Spike-Based Winner-Take-All Computation: Fundamental Limits and Order-Optimal Circuits. 2523-2561 - Philip M. Long, Hanie Sedghi:
On the Effect of the Activation Function on the Distribution of Hidden Nodes in a Deep Network. 2562-2580
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