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Neural Computation, Volume 6
Volume 6, Number 1, January 1994
- Granger G. Sutton III, James A. Reggia, Steven L. Armentrout, C. Lynne D'Autrechy:
Cortical Map Reorganization as a Competitive Process. 1-13
- Alain Destexhe, Zachary F. Mainen
, Terrence J. Sejnowski:
An Efficient Method for Computing Synaptic Conductances Based on a Kinetic Model of Receptor Binding. 14-18
- Alexander V. Lukashin, Apostolos P. Georgopoulos:
A Neural Network for Coding of Trajectories by Time Series of Neuronal Population Vectors. 19-28 - Terence D. Sanger:
Theoretical Considerations for the Analysis of Population Coding in Motor Cortex. 29-37 - Dean V. Buonomano, Michael D. Mauk:
Neural Network Model of the Cerebellum: Temporal Discrimination and the Timing of Motor Responses. 38-55 - Allan Gottschalk, Malcolm D. Ogilvie, Diethelm W. Richter, Allan I. Pack:
Computational Aspects of the Respiratory Pattern Generator. 56-68 - Thomas LoFaro
Subharmonic Coordination in Networks of Neurons with Slow Conductances. 69-84 - Ali A. Minai, William B. Levy:
Setting the Activity Level in Sparse Random Networks. 85-99 - Kenneth D. Miller, David J. C. MacKay:
The Role of Constraints in Hebbian Learning. 100-126 - Zhaoping Li, Joseph J. Atick:
Toward a Theory of the Striate Cortex. 127-146 - Barak A. Pearlmutter
Fast Exact Multiplication by the Hessian. 147-160 - Andrew H. Gee, Richard W. Prager:
Polyhedral Combinatorics and Neural Networks. 161-180
Volume 6, Number 2, March 1994
- Michael I. Jordan, Robert A. Jacobs:
Hierarchical Mixtures of Experts and the EM Algorithm. 181-214
- Gerald Tesauro:
TD-Gammon, a Self-Teaching Backgammon Program, Achieves Master-Level Play. 215-219 - L. F. Cugliandolo:
Correlated Attractors from Uncorrelated Stimuli. 220-224
- Bard Ermentrout, Nancy Kopell:
Learning of Phase Lags in Coupled Neural Oscillators. 225-241 - Mark E. Nelson:
A Mechanism for Neuronal Gain Control by Descending Pathways. 242-254 - Geoffrey J. Goodhill, Harry G. Barrow:
The Role of Weight Normalization in Competitive Learning. 255-269 - Stephen J. Roberts, Lionel Tarassenko:
A Probabilistic Resource Allocating Network for Novelty Detection. 270-284 - William Finnoff:
Diffusion Approximations for the Constant Learning Rate Backpropagation Algorithm and Resistance to Local Minima. 285-295 - Françoise Beaufays, Eric A. Wan:
Relating Real-Time Backpropagation and Backpropagation-Through-Time: An Application of Flow Graph Interreciprocity. 296-306 - Pierre Baldi, Yves Chauvin:
Smooth On-Line Learning Algorithms for Hidden Markov Models. 307-318 - Michel Benaïm
On Functional Approximation with Normalized Gaussian Units. 319-333 - Alan L. Yuille
Statistical Physics, Mixtures of Distributions, and the EM Algorithm. 334-340
Volume 6, Number 3, May 1994
- Alan L. Yuille
Statistical Physics Algorithms That Converge. 341-356
- Randall C. O'Reilly
Object Recognition and Sensitive Periods: A Computational Analysis of Visual Imprinting. 357-389
- Ning Qian:
Computing Stereo Disparity and Motion with Known Binocular Cell Properties. 390-404 - Edwin E. Munro, Larry E. Shupe, Eberhard E. Fetz:
Integration and Differentiation in Dynamic Recurrent Neural Networks. 405-419 - Chung-Ming Kuan, Kurt Hornik, Halbert White:
A Convergence Result for Learning in Recurrent Neural Networks. 420-440 - Csaba Szepesvári, László Balázs, András Lörincz:
Topology Learning Solved by Extended Objects: A Neural Network Model. 441-458 - Pascal Koiran:
Dynamics of Discrete Time, Continuous State Hopfield Networks. 459-468 - K. P. Unnikrishnan, Kootala P. Venugopal:
Alopex: A Correlation-Based Learning Algorithm for Feedforward and Recurrent Neural Networks. 469-490 - Jean-Pierre Nadal, Néstor Parga:
Duality Between Learning Machines: A Bridge Between Supervised and Unsupervised Learning. 491-508 - Hong Pi, Carsten Peterson:
Finding the Embedding Dimension and Variable Dependencies in Time Series. 509-520 - Dimitry Gorinevsky, Thomas H. Connolly:
Comparison of Some Neural Network and Scattered Data Approximations: The Inverse Manipulator Kinematics Example. 521-542 - Vera Kurková
Functionally Equivalent Feedforward Neural Networks. 543-558
Volume 6, Number 4, July 1994
- David J. Field:
What Is the Goal of Sensory Coding? 559-601
- Ernst Niebur, Florentin Wörgötter:
Design Principles of Columnar Organization in Visual Cortex. 602-614
- Geoffrey J. Goodhill, David J. Willshaw:
Elastic Net Model of Ocular Dominance: Overall Stripe Pattern and Monocular Deprivation. 615-621 - Öjvind Bernander, Christof Koch, Marius Usher:
The Effect of Synchronized Inputs at the Single Neuron Level. 622-641 - Haim Sompolinsky, Michail Tsodyks:
Segmentation by a Network of Oscillators with Stored Memories. 642-657 - Yukio Hayashi
Numerical Bifurcation Analysis of an Oscillatory Neural Network with Synchronous/Asynchronous Connections. 658-667 - J. Devin McAuley, Joseph Stampfli:
Analysis of the Effects of Noise on a Model for the Neural Mechanism of Short-Term Active Memory. 668-678 - Bard Ermentrout:
Reduction of Conductance-Based Models with Slow Synapses to Neural Nets. 679-695 - Kenji Doya
Dimension Reduction of Biological Neuron Models by Artificial Neural Networks. 696-717 - Gary M. Scott, W. Harmon Ray:
Neural Network Process Models Based on Linear Model Structures. 718-738 - Juha Karhunen:
Stability of Oja's PCA Subspace Rule. 739-747 - Man-Fung Cheung, Kevin M. Passino, Stephen Yurkovich:
Supervised Training of Neural Networks via Ellipsoid Algorithms. 748-760 - N. Scott Cardell, Wayne H. Joerding, Ying Li:
Why Some Feedforward Networks Cannot Learn Some Polynomials. 761-766
Volume 6, Number 5, September 1994
- Stephen P. Luttrell
A Bayesian Analysis of Self-Organizing Maps. 767-794 - Marius Usher, Martin Stemmler, Christof Koch, Zeev Olami:
Network Amplification of Local Fluctuations Causes High Spike Rate Variability, Fractal Firing Patterns and Oscillatory Local Field Potentials. 795-836
- Alan M. N. Fu:
Statistical Analysis of an Autoassociative Memory Network. 837-841
- Jirí Síma:
Loading Deep Networks Is Hard. 842-850 - Vladimir Vapnik, Esther Levin, Yann LeCun:
Measuring the VC-Dimension of a Learning Machine. 851-876 - Wolfgang Maass:
Neural Nets with Superlinear VC-Dimension. 877-884 - Jihong Lee:
A Novel Design Method for Multilayer Feedforward Neural Networks. 885-901 - Jean-Dominique Gascuel, Bahram Moobed, Michel Weinfeld:
An Internal Mechanism for Detecting Parasite Attractors in a Hopfield Network. 902-915 - Thorsteinn S. Rögnvaldsson
On Langevin Updating in Multilayer Perceptrons. 916-926 - Hossam Osman, Moustafa M. Fahmy:
Probabilistic Winner-Take-All Learning Algorithm for Radial-Basis-Function Neural Classifiers. 927-943 - Takashi Matsumoto, Kenji Kondo:
Realization of the "Weak Rod" by a Double Layer Parallel Network. 944-956 - Daniel J. Amit, Stefano Fusi
Learning in Neural Networks with Material Synapses. 957-982 - Pierre-Yves Burgi
Model Based on Extracellular Potassium for Spontaneous Synchronous Activity in Developing Retinas. 983-1004 - Michael S. Lewicki:
Bayesian Modeling and Classification of Neural Signals. 1005-1030
Volume 6, Number 6, November 1994
- Bartlett W. Mel:
Information Processing in Dendritic Trees. 1031-1085
- Paul A. Rhodes, Charles M. Gray:
Simulations of Intrinsically Bursting Neocortical Pyramidal Neurons. 1086-1110 - Venkatesh N. Murthy, Eberhard E. Fetz:
Effects of Input Synchrony on the Firing Rate of a Three-Conductance Cortical Neuron Model. 1111-1126 - Ying-Cheng Lai, Raimond L. Winslow, Murray B. Sachs:
The Functional Role of Excitatory and Inhibitory Interactions in Chopper Cells of the Anteroventral Cochlear Nucleus. 1127-1140 - Carlos Lourenço, Agnessa Babloyantz:
Control of Chaos in Networks with Delay: A Model for Synchronization of Cortical Tissue. 1141-1154 - Peter Manolios
First-Order Recurrent Neural Networks and Deterministic Finite State Automata. 1155-1173 - Lawrence K. Saul, Michael I. Jordan:
Learning in Boltzmann Trees. 1174-1184 - Tommi S. Jaakkola, Michael I. Jordan, Satinder P. Singh:
On the Convergence of Stochastic Iterative Dynamic Programming Algorithms. 1185-1201 - R. S. Shadafan, M. Niranjan:
A Dynamic Neural Network Architecture by Sequential Partitioning of the Input Space. 1202-1222 - Lars Kai Hansen
Pruning from Adaptive Regularization. 1223-1232 - Yoshifusa Ito:
Approximation Capability of Layered Neural Networks with Sigmoid Units on Two Layers. 1233-1243 - Motoaki Kawanabe, Shun-ichi Amari:
Estimation of Network Parameters in Semiparametric Stochastic Perceptron. 1244-1261 - Kurt Hornik
Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives. 1262-1275 - Yong Liu:
Influence Function Analysis of PCA and BCM Learning. 1276-1288 - Harris Drucker, Corinna Cortes, Lawrence D. Jackel, Yann LeCun, Vladimir Vapnik:
Boosting and Other Ensemble Methods. 1289-1301
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