yusuke1997/dblp-id-title huggingface dataset:
Modeling Basal Ganglia for Understanding Parkinsonian Reaching Movements
Least Square Regression with l p -Coefficient Regularization
Binary-oscillator networks: bridging a gap between experimental and abstract modeling of neural networks
Sparse Coding on the Spot: Spontaneous Retinal Waves Suffice for Orientation Selectivity
Learning a Sparse Code for Temporal Sequences Using STDP and Sequence Compression
Stability Against Fluctuations: Scaling, Bifurcations, and Spontaneous Symmetry Breaking in Stochastic Models of Synaptic Plasticity
Inferring Perceptual Saliency Fields from Viewpoint-Dependent Recognition Data
Recurrent Neural Network Approach Based on the Integral Representation of the Drazin Inverse
Use of a Deep Belief Network for Small High-Level Abstraction Data Sets Using Artificial Intelligence with Rule Extraction
Efficient Computation Based on Stochastic Spikes
A Competitive-Layer Model for Feature Binding and Sensory Segmentation
Failure of Motor Learning for Large Initial Errors
Gain Control by Concerted Changes in I A and I H Conductances
Analysis of Cluttered Scenes Using an Elastic Matching Approach for Stereo Images
The Approach of a Neuron Population Firing Rate to a New Equilibrium: An Exact Theoretical Result
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
Sequence Classification Using Third-Order Moments
Optimization via Intermittency with a Self-Organizing Neural Network
Enhanced Signal Detection by Adaptive Decorrelation of Interspike Intervals
Singularities in Primate Orientation Maps
From Biophysical to Integrate-and-Fire Modeling
Critical Analysis of Dimension Reduction by a Moment Closure Method in a Population Density Approach to Neural Network Modeling
Causal Discovery via Reproducing Kernel Hilbert Space Embeddings
Dense Sample Deep Learning
A Neurocomputational Approach to Prepositional Phrase Attachment Ambiguity Resolution
Bridging M/EEG Source Imaging and Independent Component Analysis Frameworks Using Biologically Inspired Sparsity Priors
A Model for Motor Endplate Morphogenesis: Diffusible Morphogens, Transmembrane Signaling, and Compartmentalized Gene Expression
Hebb-Type Dynamics is Sufficient to Account for the Inverse Magnification Rule in Cortical Somatotopy
Sparse Covariance Matrix Estimation by DCA-Based Algorithms
Identifying Functional Connectivity in Large-Scale Neural Ensemble Recordings: A Multiscale Data Mining Approach
Representations of Space and Time in the Maximization of Information Flow in the Perception-Action Loop
An Adaptive Method for Subband Decomposition ICA
Multivariate Time Series Decomposition into Oscillation Components
Improving Rejection Performance on Handwritten Digits by Training with "Rubbish"
Associative Memory in a Multimodular Network
Can Spike Coordination Be Differentiated from Rate Covariation?
A simple spike train decoder inspired by the sampling theorem
Nonlinear Memory Capacity of Parallel Time-Delay Reservoir Computers in the Processing of Multidimensional Signals
Graph Clustering With Graph Capsule Network
Might a Single Neuron Solve Interesting Machine Learning Problems Through Successive Computations on Its Dendritic Tree?
Learning Intention-Aware Policies in Deep Reinforcement Learning
Systematic Fluctuation Expansion for Neural Network Activity Equations
Methods for Assessment of Memory Reactivation
A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures
An Infomax Algorithm Can Perform Both Familiarity Discrimination and Feature Extraction in a Single Network
Modeling Multivariate Time Series on Manifolds with Skew Radial Basis Functions
Smooth On-Line Learning Algorithms for Hidden Markov Models
Modeling the Correlated Activity of Neural Populations: A Review
Finite State Automata and Simple Recurrent Networks
Information-Theoretic Bounds and Approximations in Neural Population Coding
On Some Classes of Sequential Spiking Neural P Systems
Emergence of Optimal Decoding of Population Codes Through STDP
Correction to 'Lower Bounds on the VC-Dimension of Smoothly Parametrized Function Classes'
Bayesian Optimization for Cascade-Type Multistage Processes
Robustness in Multilayer Perceptrons
Effect of Reference Scheme on Power and Phase of the Local Field Potential
Online Adaptive Decision Trees
A self-organizing neural network for the traveling salesman problem that is competitive with simulated annealing
Analyzing and Accelerating the Bottlenecks of Training Deep SNNs With Backpropagation
Two Timescale Analysis of the Alopex Algorithm for Optimization
Asymptotic Convergence Rate of the EM Algorithm for Gaussian Mixtures
A Generalized Framework of Multifidelity Max-Value Entropy Search Through Joint Entropy
Introducing asymmetry into interneuron learning
Stochastic Optimal Control as a Theory of Brain-Machine Interface Operation
Spontaneous excitations in the visual cortex: stripes, spirals, rings, and collective bursts
Averaging Regularized Estimators
The Benefits of Modeling Slack Variables in SVMs
The Successor Representation and Temporal Context
Introducing User-Prescribed Constraints in Markov Chains for Nonlinear Dimensionality Reduction
Learning and generalization with Minimerror, a temperature-dependent learning algorithm
On the Role of Biophysical Properties of Cortical Neurons in Binding and Segmentation of Visual Scenes
Probabilistic Winner-Take-All Learning Algorithm for Radial-Basis-Function Neural Classifiers
Orthogonal Connectivity Factorization: Interpretable Decomposition of Variability in Correlation Matrices
A Unifying Review of Linear Gaussian Models
Note on the Maxnet Dynamics
Enhancing Density-Based Data Reduction Using Entropy
Orthogonality of Decision Boundaries in Complex-Valued Neural Networks
A Finite-Sample, Distribution-Free, Probabilistic Lower Bound on Mutual Information
A Complementarity Mechanism for Enhanced Pattern Processing
An Online Structural Plasticity Rule for Generating Better Reservoirs
Integration of Reinforcement Learning and Optimal Decision-Making Theories of the Basal Ganglia
Advancing System Performance with Redundancy: From Biological to Artificial Designs
Asymptotic Theory of Information-Theoretic Experimental Design
Capacity Limitations of Visual Search in Deep Convolutional Neural Networks
Point-Process Principal Components Analysis via Geometric Optimization
A Neural Network Architecture for Visual Selection
Learning the Nonlinearity of Neurons from Natural Visual Stimuli
Spike Train Processing by a Silicon Neuromorph: The Role of Sublinear Summation in Dendrites
Spherical Mesh Adaptive Direct Search for Separating Quasi-Uncorrelated Sources by Range-Based Independent Component Analysis
ASIC Implementation of a Nonlinear Dynamical Model for Hippocampal Prosthesis
Theory and Algorithm for Learning with Dissimilarity Functions
A Novel Design Method for Multilayer Feedforward Neural Networks
Diffusive Information Accumulation by Minimal Recurrent Neural Models of Decision Making
A Learning Rule for Local Synaptic Interactions Between Excitation and Shunting Inhibition
Neural Modeling of an Internal Clock
Quantifying Statistical Interdependence by Message Passing on Graphs - Part II: Multidimensional Point Processes
Active Inference: A Process Theory
Stochastic Multichannel Ranking with Brain Dynamics Preferences
Role of Temporal Integration and Fluctuation Detection in the Highly Irregular Firing of a Leaky Integrator Neuron Model with Partial Reset
Accurate On-line Support Vector Regression
Transductive Methods for the Distributed Ensemble Classification Problem
Adaptive Blind Separation with an Unknown Number of Sources
Computing with Spikes: The Advantage of Fine-Grained Timing
Errata to "Bayesian Community Detection" ( Neural Computation , Sept. 2012 , Vol. 24, No. 9: 2434-2456)
A New Foreperiod Effect on Intertrial Phase Coherence. Part I: Existence and Behavioral Relevance
Analysis of the Stabilized Supralinear Network
Cross-Correlations in High-Conductance States of a Model Cortical Network
The Ornstein-Uhlenbeck Process Does Not Reproduce Spiking Statistics of Neurons in Prefrontal Cortex
Architectural Bias in Recurrent Neural Networks: Fractal Analysis
Hidden Markov Models Predict the Future Choice Better Than a PSTH-Based Method
Exponential or Polynomial Learning Curves? Case-Based Studies
Stimulus-Dependent Synchronization of Neuronal Assemblies
Pacemaker-Induced Coherence in Cortical Networks
Coding of Temporally Varying Signals in Networks of Spiking Neurons with Global Delayed Feedback
Orientation Tuning Properties of Simple Cells in Area V1 Derived from an Approximate Analysis of Nonlinear Neural Field Models
On the Dynamical Interplay of Positive and Negative Affects
Fast Recursive Filters for Simulating Nonlinear Dynamic Systems
Temporal Evolution of Generalization during Learning in Linear Networks
A New Discriminative Kernel from Probabilistic Models
Architecture-Independent Approximation of Functions
Nonconvex Sparse Regularization for Deep Neural Networks and Its Optimality
Sequential Monte Carlo Methods to Train Neural Network Models
Multiple Model-Based Reinforcement Learning
Strictly Positive-Definite Spike Train Kernels for Point-Process Divergences
Toward Training Recurrent Neural Networks for Lifelong Learning
Vergence Dynamics Predict Fixation Disparity
A Maximum Likelihood Approach to Density Estimation with Semidefinite Programming
Normalization Enables Robust Validation of Disparity Estimates from Neural Populations
A Simple Model of Long-Term Spike Train Regularization
Predictive Coding, Variational Autoencoders, and Biological Connections
Spike-Timing-Dependent Plasticity in Balanced Random Networks
The Brain Binds Entities and Events by Multiregional Activation from Convergence Zones
Multispike Interactions in a Stochastic Model of Spike-Timing-Dependent Plasticity
Storage Capacity of Quaternion-Valued Hopfield Neural Networks With Dual Connections
Hyperparameter Selection for Self-Organizing Maps
A Neural Network That Learns to Interpret Myocardial Planar Thallium Scintigrams
Causal Inference on Discrete Data via Estimating Distance Correlations
Encoding and Decoding Spikes for Dynamic Stimuli
Recurrent Backpropagation and the Dynamical Approach to Adaptive Neural Computation
Breaking Rotational Symmetry in a Self-Organizing Map-Model for Orientation Map Development
Emergence of Memory-Driven Command Neurons in Evolved Artificial Agents
Topographic Product Models Applied to Natural Scene Statistics
Fusion of Scores in a Detection Context Based on Alpha Integration
Subtractive and Divisive Inhibition: Effect of Voltage-Dependent Inhibitory Conductances and Noise
Backward Projections in the Cerebral Cortex: Implications for Memory Storage
Optimality and Saturation in Axonal Chemotaxis
On the Analysis and Interpretation of Inhomogeneous Quadratic Forms as Receptive Fields
Finding the Embedding Dimension and Variable Dependencies in Time Series
Improvements to the Sensitivity of Gravitational Clustering for Multiple Neuron Recordings
Second-Order Learning Algorithm with Squared Penalty Term
Toward Improving the Generation Quality of Autoregressive Slot VAEs
Synchrony in Heterogeneous Networks of Spiking Neurons
A Self-Organized Neural Comparator
Segmentation, Binding, and Illusory Conjunctions
Dynamical Mechanism for Sharp Orientation Tuning in an Integrate-and-Fire Model of a Cortical Hypercolumn
Cognitive Map Formation Through Sequence Encoding by Theta Phase Precession
Quickly Generating Representative Samples from an RBM-Derived Process
Taming Fluctuations in a Stochastic Model of Spike-Timing-Dependent Plasticity
On Embedding Synfire Chains in a Balanced Network
On Convergence Conditions of an Extended Projection Neural Network
Training a Sigmoidal Node Is Hard
Analysis of Complete Stability for Discrete-Time Cellular Neural Networks with Piecewise Linear Output Functions
The Upward Bias in Measures of Information Derived from Limited Data Samples
Modeling Mental Navigation in Scenes with Multiple Objects
A Framework for Evaluating Pairwise and Multiway Synchrony Among Stimulus-Driven Neurons
Optimal Approximation of Signal Priors
An Effective Bayesian Neural Network Classifier with a Comparison Study to Support Vector Machine
Robust Full Bayesian Learning for Radial Basis Networks
Learning Invariant Features in Modulatory Networks through Conflict and Ambiguity
Multiple Tests Based on a Gaussian Approximation of the Unitary Events Method with Delayed Coincidence Count
Hierarchical Error Representation: A Computational Model of Anterior Cingulate and Dorsolateral Prefrontal Cortex
Covariance Learning of Correlated Patterns in Competitive Networks
A Neural Model of the Scintillating Grid Illusion: Disinhibition and Self-Inhibition in Early Vision
Adaptive Decoding for Brain-Machine Interfaces Through Bayesian Parameter Updates
Estimating Scale-Invariant Future in Continuous Time
A Model for Fast Analog Computation Based on Unreliable Synapses
Integration of Stochastic Models by Minimizing alpha -Divergence
Complexity Optimized Data Clustering by Competitive Neural Networks
Biologically Realistic Mean-Field Models of Conductance-Based Networks of Spiking Neurons with Adaptation
Setting the Activity Level in Sparse Random Networks
Dendrites Enable a Robust Mechanism for Neuronal Stimulus Selectivity
Online Pairwise Learning Algorithms
Neural Model of Coding Stimulus Orientation and Adaptation
Hyperbolically Discounted Temporal Difference Learning
Quantifying Information Conveyed by Large Neuronal Populations
Density-Weighted Nyström Method for Computing Large Kernel Eigensystems
Identifying and Localizing Multiple Objects Using Artificial Ventral and Dorsal Cortical Visual Pathways
A Novel Optimization Framework to Improve the Computational Cost of Muscle Activation Prediction for a Neuromusculoskeletal System
Higher-Order Statistics of Input Ensembles and the Response of Simple Model Neurons
Difficulty of Singularity in Population Coding
Comments and Correction on " U -Processes and Preference Learning" ( Neural Computation Vol. 26, pp. 2896-2924, 2014)
A Simple Network Showing Burst Synchronization without Frequency Locking
What Is the Limit of Redundancy Reduction with Divisive Normalization?
Adding Space to Random Networks of Spiking Neurons: A Method Based on Scaling the Network Size
Hebbian Imprinting and Retrieval in Oscillatory Neural Networks
ℓ 1 -Regularized ICA: A Novel Method for Analysis of Task-Related fMRI Data
Multiview Alignment and Generation in CCA via Consistent Latent Encoding
Feature Selection via Coalitional Game Theory
A Polynomial Time Algorithm for Generating Neural Networks for Pattern Classification: Its Stability Properties and Some Test Results
Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning
Recurrent Information Optimization with Local, Metaplastic Synaptic Dynamics
A Unifying Framework of Synaptic and Intrinsic Plasticity in Neural Populations
The Costs of Ignoring High-Order Correlations in Populations of Model Neurons
Narrow vs Wide Tuning Curves: What's Best for a Population Code?
A Competitive Distribution Theory of Neocortical Dynamics
Temporal Coding of Time-Varying Stimuli
Synchrony and Desynchrony in Integrate-and-Fire Oscillators
Competitive STDP Learning of Overlapping Spatial Patterns
Flexible Frequency Switching in Adult Mouse Visual Cortex Is Mediated by Competition Between Parvalbumin and Somatostatin Expressing Interneurons
Synchrony in excitatory neural networks
Sampled-Data State Feedback Stabilization of Boolean Control Networks
Spike-Centered Jitter Can Mistake Temporal Structure
Multiorder Neurons for Evolutionary Higher-Order Clustering and Growth
The Role of Constraints in Hebbian Learning
Generalized Discriminant Analysis Using a Kernel Approach
A Dynamic Causal Model of the Coupling Between Pulse Stimulation and Neural Activity
Evolution of Time Coding Systems
A Predictive Processing Model of Episodic Memory and Time Perception
Boundedness and Stability for Integrodifferential Equations Modeling Neural Field with Time Delay
On the Phase Reduction and Response Dynamics of Neural Oscillator Populations
Fields as Limit Functions of Stochastic Discrimination and Their Adaptability
Airline Crew Scheduling With Potts Neurons
Recurrent Sampling Models for the Helmholtz Machine
Erratum ("A State-Space Analysis for Reconstruction of Goal-Directed Movements Using Neural Signals" Neural Computation, Volume 18, Number 10, pp. 2465-2494)
Asynchronous Event-Based Motion Processing: From Visual Events to Probabilistic Sensory Representation
Robust Classifiers without Robust Features
A Unified Approach to the Study of Temporal, Correlational, and Rate Coding
Bayesian Integration in a Spiking Neural System for Sensorimotor Control
Efficient Decoding of Large-Scale Neural Population Responses With Gaussian-Process Multiclass Regression
Gauge-Optimal Approximate Learning for Small Data Classification
New Models for Motor Control
Machine Learning: Deepest Learning as Statistical Data Assimilation Problems
Impact of Spike Train Autostructure on Probability Distribution of Joint Spike Events
A Self-Organizing Neural Network Architecture for Navigation Using Optic Flow
Operant Matching as a Nash Equilibrium of an Intertemporal Game
Transmission of Population-Coded Information
Temporal Sequence Learning, Prediction, and Control: A Review of Different Models and Their Relation to Biological Mechanisms
Neural Network Pruning with Tukey-Kramer Multiple Comparison Procedure
On the Realization of a Kolmogorov Network
From Univariate to Multivariate Coupling Between Continuous Signals and Point Processes: A Mathematical Framework
On the Analytical Solution of Firing Time for SpikeProp
Computing with the Leaky Integrate-and-Fire Neuron: Logarithmic Computation and Multiplication
Semilinear Predictability Minimization Produces Well-Known Feature Detectors
Multiple Timescale Online Learning Rules for Information Maximization with Energetic Constraints
Facet Annotation by Extending CNN with a Matching Strategy
Heuristic Tree-Partition-Based Parallel Method for Biophysically Detailed Neuron Simulation
The Relationship Between Synchronization Among Neuronal Populations and Their Mean Activity Levels
On the Approximation Rate of Hierarchical Mixtures-of-Experts for Generalized Linear Models
Nonlinear Autoassociation Is Not Equivalent to PCA
Topological Sparse Learning of Dynamic Form Patterns
One-Bit-Matching Conjecture for Independent Component Analysis
Vectorized Algorithms for Spiking Neural Network Simulation
Extracting Oscillations: Neuronal Coincidence Detection with Noisy Periodic Spike Input
The Whitney Reduction Network: A Method for Computing Autoassociative Graphs
The Evolution of Representation in Simple Cognitive Networks
The Astrocyte as a Gatekeeper of Synaptic Information Transfer
The Firing of an Excitable Neuron in the Presence of Stochastic Trains of Strong Synaptic Inputs
How Synaptic Release Probability Shapes Neuronal Transmission: Information-Theoretic Analysis in a Cerebellar Granule Cell
Comparison of Model Selection for Regression
Approximation Bounds for Some Sparse Kernel Regression Algorithms
Minimal Model for Intracellular Calcium Oscillations and Electrical Bursting in Melanotrope Cells of Xenopus Laevis
Learning Intermediate-Level Representations of Form and Motion from Natural Movies
Neural Network Models for Conditional Distribution Under Bayesian Analysis
Simplicity and Efficiency of Integrate-and-Fire Neuron Models
Bifurcation Analysis of Jansen's Neural Mass Model
An SMO Algorithm for the Potential Support Vector Machine
Binding and Normalization of Binary Sparse Distributed Representations by Context-Dependent Thinning
A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression
Confidence-Controlled Hebbian Learning Efficiently Extracts Category Membership From Stimuli Encoded in View of a Categorization Task
Faithful Representation Of Separable Input Distributions
Selecting Informative Data for Developing Peptide-MHC Binding Predictors Using a Query by Committee Approach
Approximating the Architecture of Visual Cortex in a Convolutional Network
Nonholonomic Orthogonal Learning Algorithms for Blind Source Separation
Long-Term Reward Prediction in TD Models of the Dopamine System
A Quantitative Study of Fault Tolerance, Noise Immunity, and Generalization Ability of MLPs
Learning Tetris Using the Noisy Cross-Entropy Method
Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model
Feature Extraction Through LOCOCODE
Dynamics of Learning in MLP: Natural Gradient and Singularity Revisited
Training a Hyperdimensional Computing Classifier Using a Threshold on Its Confidence
Markov Chain Monte Carlo Methods for State-Space Models with Point Process Observations
MISEP Method for Postnonlinear Blind Source Separation
Payoff-Monotonic Game Dynamics and the Maximum Clique Problem
Active Learning for Enumerating Local Minima Based on Gaussian Process Derivatives
Mechanisms That Modulate the Transfer of Spiking Correlations
Incremental Slow Feature Analysis: Adaptive Low-Complexity Slow Feature Updating from High-Dimensional Input Streams
Influence Function Analysis of PCA and BCM Learning
The Problem of Rapid Variable Creation
Arbitrary Elastic Topologies and Ocular Dominance
A Hierarchy of Associations in Hippocampo-Cortical Systems: Cognitive Maps and Navigation Strategies
Parameter Identification Problem in the Hodgkin-Huxley Model
Dimensionality of Object Representations in Monkey Inferotemporal Cortex
Automatic Spike Sorting Using Tuning Information
Spike-Frequency Adapting Neural Ensembles: Beyond Mean Adaptation and Renewal Theories
Variable Timescales of Repeated Spike Patterns in Synfire Chain with Mexican-Hat Connectivity
Spatiotemporal Coding in the Cortex: Information Flow-Based Learning in Spiking Neural Networks
A Fast And Robust Cluster Update Algorithm For Image Segmentation In Spin-Lattice Models Without Annealing - Visual Latencies Revisited
Optimal Multivariate Tuning with Neuron-Level and Population-Level Energy Constraints
Gaussian Processes for Classification: Mean-Field Algorithms
Asymptotic Behavior of Periodic Cohen-Grossberg Neural Networks with Delays
ParceLiNGAM: A Causal Ordering Method Robust Against Latent Confounders
A Counterexample to Temporal Differences Learning
Mixture Models Based on Neural Network Averaging
On the Complexity of Logistic Regression Models
MLP in Layer-Wise Form with Applications to Weight Decay
Energy-Efficient Neuromorphic Classifiers
A Volatility Measure for Annealing in Feedback Neural Networks
A Generalized Divergence Measure for Nonnegative Matrix Factorization
Analog Versus Digital: Extrapolating from Electronics to Neurobiology
Bayesian Trigonometric Support Vector Classifier
Error Estimation by Series Association for Neural Network Systems
Learning to Recognize Three-Dimensional Objects
An Autoassociative Neural Network Model of Paired-Associate Learning
The Variance of Covariance Rules for Associative Matrix Memories and Reinforcement Learning
Machine-Learning-Based Coadaptive Calibration for Brain-Computer Interfaces
Temporal Decoding by Phase-Locked Loops: Unique Features of Circuit-Level Implementations and Their Significance for Vibrissal Information Processing
Local and Global Gating of Synaptic Plasticity
Variations on the Theme of Synaptic Filtering: A Comparison of Integrate-and-Express Models of Synaptic Plasticity for Memory Lifetimes
Recognizing Hand-Printed Letters and Digits Using Backpropagation Learning
Adaptive On-line Learning Algorithms for Blind Separation-Maximization Entropy and Minimum Mutual Information
Natural Gradient Learning for Over- and Under-Complete Bases in ICA
Bayesian Active Learning of Neural Firing Rate Maps with Transformed Gaussian Process Priors
Effect of Binocular Cortical Misalignment on Ocular Dominance and Orientation Selectivity
Deep Restricted Kernel Machines Using Conjugate Feature Duality
Weak, Stochastic Temporal Correlation of Large-Scale Synaptic Input Is a Major Determinant of Neuronal Bandwidth
Local and Global Gestalt Laws: A Neurally Based Spectral Approach
High-Order Constrasts for Independent Component Analysis
Spontaneous Clustering via Minimum Gamma-Divergence