yusuke1997/dblp-id-title huggingface dataset:
An Adaptive Bayesian Pruning for Neural Networks in a Non-Stationary Environment
Information Geometry of Mean-Field Approximation
A New On-Line Learning Model
Sparse On-Line Gaussian Processes
Toward Unified Hybrid Simulation Techniques for Spiking Neural Networks
Realizing Active Inference in Variational Message Passing: The Outcome-Blind Certainty Seeker
Multiclass Alpha Integration of Scores from Multiple Classifiers
Learning Coefficients of Layered Models When the True Distribution Mismatches the Singularities
A Note on the Decomposition Methods for Support Vector Regression
Information Transfer Between Rhythmically Coupled Networks: Reading the Hippocampal Phase Code
Hierarchical Dynamical Model for Multiple Cortical Neural Decoding
Estimating Phase From Observed Trajectories Using the Temporal 1-Form
Correlated Firing in a Feedforward Network with Mexican-Hat-Type Connectivity
Expansion of Information in the Binary Autoencoder With Random Binary Weights
Risk-Aware Control
The interchangeability of learning rate and gain in backpropagation neural networks
A Lagrange Multiplier and Hopfield-Type Barrier Function Method for the Traveling Salesman Problem
MOSAIC for Multiple-Reward Environments
A Gradient Learning Rule for the Tempotron
Optimal Signal Estimation in Neuronal Models
Evaluating Auditory Performance Limits: I. One-Parameter Discrimination Using a Computational Model for the Auditory Nerve
A Novel Nonparametric Approach for Neural Encoding and Decoding Models of Multimodal Receptive Fields
A Further Result on the ICA One-Bit-Matching Conjecture
Supervised Networks Which Self-Organize Class Outputs
The Effect of Synchronized Inputs at the Single Neuron Level
Invariant Object Recognition in the Visual System with Novel Views of 3D Objects
A Computational Model of the Functional Role of the Ventral-Striatal D2 Receptor in the Expression of Previously Acquired Behaviors
Simplifying Neural Networks by Soft Weight-Sharing
Replay as a Basis for Backpropagation Through Time in the Brain
Optimal Schedules in Multitask Motor Learning
Pruning with Replacement on Limited Resource Allocating Networks by F-Projections
The Faulty Behavior of Feedforward Neural Networks with Hard-limiting Activation Fuction
Visuomotor Mismatch Responses as a Hallmark of Explaining Away in Causal Inference
Dynamics and Reliability of Bistable Neurons Driven with Time-Dependent Stimuli
Dynamics and Formation of Self-Organizing Maps
Block-Regularized m × 2 Cross-Validated Estimator of the Generalization Error
Exhaustive Learning
A Cooperative Recurrent Neural Network for Solving L 1 Estimation Problems with General Linear Constraints
The Effects of Input Rate and Synchrony on a Coincidence Detector: Analytical Solution
Active Classification With Uncertainty Comparison Queries
Backpropagation Applied to Handwritten Zip Code Recognition
Increasing Memory Capacity and Reducing Spurious States in Neural Networks by Introducing Coherent and Collective Firing
Evidence Accumulation and Change Rate Inference in Dynamic Environments
Decorrelated Hebbian Learning for Clustering and Function Approximation
Singularities Affect Dynamics of Learning in Neuromanifolds
Nonnegative Matrix Factorization with Rank Regularization and Hard Constraint
Indexed Families of Functionals and Gaussian Radial Basis Functions
Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks
Kalman Filter Implementation of Self-Organizing Feature Maps
Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures
Detecting and Estimating Signals in Noisy Cable Structures, I: Neuronal Noise Sources
Measuring Information Spatial Densities
An Efficient Gradient-Based Algorithm for On-Line Training of Recurrent Network Trajectories
Maximum Likelihood Topographic Map Formation
Data Clustering Using a Model Granular Magnet
An Algorithm of Supervised Learning for Multilayer Neural Networks
Populations of Tightly Coupled Neurons: The RGC/LGN System
The Computational Power of Interactive Recurrent Neural Networks
Enhanced 3D Shape Recovery Using the Neural-Based Hybrid Reflectance Model
A Combinatorial Model for Dentate Gyrus Sparse Coding
Receptive Field Self-Organization in a Model of the Fine Structure in V1 Cortical Columns
Predicting the Ease of Human Category Learning Using Radial Basis Function Networks
Topology and Geometry of Single Hidden Layer Network, Least Squares Weight Solutions
Posterior Weighted Reinforcement Learning with State Uncertainty
Constructive Incremental Learning from Only Local Information
Products of Gaussians and Probabilistic Minor Component Analysis
Context Learning in the Rodent Hippocampus
Accelerated Spike Resampling for Accurate Multiple Testing Controls
Nonlinear and Noisy Extension of Independent Component Analysis: Theory and Its Application to a Pitch Sensation Model
Neuronal Assembly Dynamics in Supervised and Unsupervised Learning Scenarios
A Measurement Fusion Method for Nonlinear System Identification Using a Cooperative Learning Algorithm
The Perils of Being Unhinged: On the Accuracy of Classifiers Minimizing a Noise-Robust Convex Loss
A Predictive-Coding Network That Is Both Discriminative and Generative
Neurogammon Wins Computer Olympiad
Efficient Block Training of Multilayer Perceptrons
Loading Deep Networks Is Hard
Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
An Exponential Response Neural Net
A Connection Between Score Matching and Denoising Autoencoders
Hardware-Amenable Structural Learning for Spike-Based Pattern Classification Using a Simple Model of Active Dendrites
A DC Programming Approach for Finding Communities in Networks
Multinomial Bayesian Learning for Modeling Classical and Nonclassical Receptive Field Properties
System Identification of mGluR-Dependent Long-Term Depression
Bayesian Self-Organization Driven by Prior Probability Distributions
Continuation-Based Numerical Detection of After-Depolarization and Spike-Adding Thresholds
Analysis of Sparse Representation and Blind Source Separation
Oscillatory Neural Networks with Self-Organized Segmentation of Overlapping Patterns
On a Scalable Entropic Breaching of the Overfitting Barrier for Small Data Problems in Machine Learning
Echo-Enhanced Embodied Visual Navigation
Sensitivity to Stimulus Irregularity Is Inherent in Neural Networks
Active Role of Self-Sustained Neural Activity on Sensory Input Processing: A Minimal Theoretical Model
First Passage Time Memory Lifetimes for Multistate, Filter-Based Synapses
Complex Scheduling with Potts Neural Networks
Recursive Finite Newton Algorithm for Support Vector Regression in the Primal
Efficient Coding of Time-Relative Structure Using Spikes
Electrical Signaling Beyond Neurons
Promoting the Shift From Pixel-Level Correlations to Object Semantics Learning by Rethinking Computer Vision Benchmark Data Sets
Fast and Robust Learning by Reinforcement Signals: Explorations in the Insect Brain
Dynamics of Deterministic and Stochastic Paired Excitatory-Inhibitory Delayed Feedback
Online Learning in Radial Basis Function Networks
Power Function Error Initialization Can Improve Convergence of Backpropagation Learning in Neural Networks for Classification
Improving Spiking Dynamical Networks: Accurate Delays, Higher-Order Synapses, and Time Cells
Object Discrimination Based on Depth-from-Occlusion
New Supervised Learning Theory Applied to Cerebellar Modeling for Suppression of Variability of Saccade End Points
Implicit Contact Dynamics Modeling With Explicit Inertia Matrix Representation for Real-Time, Model-Based Control in Physical Environment
A Simplified Neural-Network Solution through Problem Decomposition: The Case of the Truck Backer-Upper
Nonequilibrium Statistical Mechanics of Continuous Attractors
Optimizing One-Shot Learning with Binary Synapses
Learning by Kernel Polarization
Chaotic Frequency Scaling in a Coupled Oscillator Model for Free Rhythmic Actions
On Different Facets of Regularization Theory
Ambient GABA Responsible for Age-Related Changes in Multistable Perception
Generation of Synthetic Spike Trains with Defined Pairwise Correlations
Nonlocal Estimation of Manifold Structure
A Computational Model of Lateralization and Asymmetries in Cortical Maps
Learning the Lie Groups of Visual Invariance
Adaptive Learning Neural Network Method for Solving Time-Fractional Diffusion Equations
An Adjustment to the Time-Rescaling Method for Application to Short-Trial Spike Train Data
Polychronization: Computation with Spikes
Asymmetric Weights and Retrieval Practice in an Autoassociative Neural Network Model of Paired-Associate Learning
Marr's Theory of the Neocortex as a Self-Organizing Neural Network
An Overview of the Free Energy Principle and Related Research
Analytical Integrate-and-Fire Neuron Models with Conductance-Based Dynamics for Event-Driven Simulation Strategies
Neural Integrator: A Sandpile Model
Associative Memory with Dynamic Synapses
Why Does the Somatosensory Homunculus Have Hand Next to Face and Feet Next to Genitals?: An Hypothesis
Independent Vector Analysis for Source Separation Using a Mixture of Gaussians Prior
A Fast p Spike Alignment Metric
Exact Simulation of Integrate-and-Fire Models with Synaptic Conductances
Correlation Between Uncoupled Conductance-Based Integrate-and-Fire Neurons Due to Common and Synchronous Presynaptic Firing
Olfactory Recognition Based on EEG Gamma-Band Activity
Estimating Parameters of Generalized Integrate-and-Fire Neurons from the Maximum Likelihood of Spike Trains
Generation of Correlated Spike Trains
Low-Rank, High-Order Tensor Completion via t- Product-Induced Tucker (tTucker) Decomposition
Recurrent Kernel Machines: Computing with Infinite Echo State Networks
An Image Analysis Algorithm for Dendritic Spines
Improved Integral Equation Solution for the First Passage Time of Leaky Integrate-and-Fire Neurons
Discriminative Learning of Propagation and Spatial Pattern for Motor Imagery EEG Analysis
Factor Analysis Using Delta-Rule Wake-Sleep Learning
Gradient-Based Optimization of Hyperparameters
Asynchronous States and the Emergence of Synchrony in Large Networks of Interacting Excitatory and Inhibitory Neurons
A Floating Gate MOS Implementation of Resistive Fuse
Large-Scale Algorithmic Search Identifies Stiff and Sloppy Dimensions in Synaptic Architectures Consistent With Murine Neocortical Wiring
Invariant Global Motion Recognition in the Dorsal Visual System: A Unifying Theory
On Nonnegative Matrix Factorization Algorithms for Signal-Dependent Noise with Application to Electromyography Data
Robust Subspace Discovery via Relaxed Rank Minimization
Higher-Order Approximations for Testing Neglected Nonlinearity
Spectral Algorithms for Supervised Learning
Gaussian Process Koopman Mode Decomposition
Simple-Cell-Like Receptive Fields Maximize Temporal Coherence in Natural Video
Modeling Cross-Modal Enhancement and Modality-Specific Suppression in Multisensory Neurons
Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatiotemporal Scales RNN Model
Extraction of Specific Signals with Temporal Structure
A Bayesian Analysis of Self-Organizing Maps
Improving the Accuracy of an Artificial Neural Network Using Multiple Differently Trained Networks
Analytical and Simulation Results for the Stochastic Spatial Fitzhugh-Nagumo Model Neuron
A Framework of Learning Through Empirical Gain Maximization
Formal Modeling of Robot Behavior with Learning
Mapping Low-Dimensional Dynamics to High-Dimensional Neural Activity: A Derivation of the Ring Model From the Neural Engineering Framework
Analysis of Online Composite Mirror Descent Algorithm
Tensor Representation of Topographically Organized Semantic Spaces
Stimulus-Dependent Correlations in Threshold-Crossing Spiking Neurons
Noise Adaptation in Integrate -and -Fire Neurons
A Statistical Theory of Long-Term Potentiation and Depression
A Robust Information Clustering Algorithm
Noise Injection: Theoretical Prospects
Identifying Functional Bases for Multidimensional Neural Computations
Short-Term Synaptic Plasticity Can Enhance Weak Signal Detectability in Nonrenewal Spike Trains
Analytic Expressions for Rate and CV of a Type I Neuron Driven by White Gaussian Noise
A Reproducing Kernel Hilbert Space Framework for Spike Train Signal Processing
Learning to Control Fast-Weight Memories: An Alternative to Dynamic Recurrent Networks
Supervised Learning Through Neuronal Response Modulation
Energy-Efficient Coding with Discrete Stochastic Events
Short-Term Synaptic Plasticity and Network Behavior
Muscle Synergy-Driven Robust Motion Control
Stimulus-Dependent Correlations and Population Codes
Active Inference, Curiosity and Insight
Learning to Design Synergetic Computers with an Extended Symmetric Diffusion Network
Quantifying Statistical Interdependence, Part III: N > 2 Point Processes
Predictive minimum description length criterion for time series modeling with neural networks
Reading Neuronal Synchrony with Depressing Synapses
Sampling Properties of the Spectrum and Coherency of Sequences of Action Potentials
Modern Artificial Neural Networks: Is Evolution Cleverer?
Firing Variability Is Higher than Deduced from the Empirical Coefficient of Variation
Distributed Control of Uncertain Systems Using Superpositions of Linear Operators
A Model of Semantic Completion in Generative Episodic Memory
Realization of the "Weak Rod" by a Double Layer Parallel Network
Solving Constraint-Satisfaction Problems with Distributed Neocortical-Like Neuronal Networks
Visual Tracking Using Neuromorphic Asynchronous Event-Based Cameras
Analysis and Design of Associative Memories Based on Recurrent Neural Networks with Linear Saturation Activation Functions and Time-Varying Delays
On Synchrony of Weakly Coupled Neurons at Low Firing Rate
Geometrical Properties of Nu Support Vector Machines with Different Norms
The Variational Gaussian Approximation Revisited
Are Loss Functions All the Same?
Effects of Synaptic Synchrony on the Neuronal Input-Output Relationship
A Model for the Action of NMDA Conductances in the Visual Cortex
Synchrony of Neuronal Oscillations Controlled by GABAergic Reversal Potentials
Improving Generalization Capabilities of Dynamic Neural Networks
Spatiochromatic Receptive Field Properties Derived from Information-Theoretic Analyses of Cone Mosaic Responses to Natural Scenes
Recurrent Cerebellar Loops Simplify Adaptive Control of Redundant and Nonlinear Motor Systems
A Spiking Neuron as Information Bottleneck
Distance-Based Logistic Matrix Factorization
Lower Bounds on the VC Dimension of Smoothly Parameterized Function Classes
Generalization and Approximation Capabilities of Multilayer Networks
Multistability of Delayed Recurrent Neural Networks with Mexican Hat Activation Functions
Inheritance of Hippocampal Place Fields Through Hebbian Learning: Effects of Theta Modulation and Phase Precession on Structure Formation
The Time-Rescaling Theorem and Its Application to Neural Spike Train Data Analysis
On a Fast, Compact Approximation of the Exponential Function
Probability Density Estimation Using Entropy Maximization
Have Brain Dynamics Evolved? Should We Look for Unique Dynamics in the Sapient Species?
Competitive Layer Model of Discrete-Time Recurrent Neural Networks with LT Neurons
Similarity, Connectionism, and the Problem of Representation in Vision
A Model for Learning Topographically Organized Parts-Based Representations of Objects in Visual Cortex: Topographic Nonnegative Matrix Factorization
Two-Dimensional Motion Perception in Flies
Time-Skew Hebb rule in a nonisopotential neuron
The Mean Time to Express Synaptic Plasticity in Integrate-and-Express, Stochastic Models of Synaptic Plasticity Induction
A Canonical Neural Circuit for Cortical Nonlinear Operations
Neural network models of perceptual learning of angle discrimination
Neuronal Spike Train Entropy Estimation by History Clustering
Fast Calculation of Synaptic Conductances
A Solution for Two-Dimensional Mazes with Use of Chaotic Dynamics in a Recurrent Neural Network Model
Connection Topology Selection in Central Pattern Generators by Maximizing the Gain of Information
Attraction Radii in Binary Hopfield Nets are Hard to Compute
Spike Timing Precision and Neural Error Correction: Local Behavior
Reliability of Information-Based Integration of EEG and fMRI Data: A Simulation Study
Many-Layered Learning
Projected Gradient Methods for Nonnegative Matrix Factorization
Validation-Based Sparse Gaussian Process Classifier Design
Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities
Role of Homeostasis in Learning Sparse Representations
Sigmoids Distinguish More Efficiently Than Heavisides
A Principle for Learning Egocentric-Allocentric Transformation
An Accurate Measure of the Instantaneous Discharge Probability, with Application to Unitary Joint-Event Analysis
A Sparse Reformulation of the Green's Function Formalism Allows Efficient Simulations of Morphological Neuron Models
Neural Representation of Space Using Sinusoidal Arrays
Gram - Schmidt Neural Nets
The Number of Synaptic Inputs and the Synchrony of Large, Sparse Neuronal Networks
Mean-Field Approximations With Adaptive Coupling for Networks With Spike-Timing-Dependent Plasticity
Rat Prefrontal Cortex Inactivations during Decision Making Are Explained by Bistable Attractor Dynamics
A Multiscale Correlation of Wavelet Coefficients Approach to Spike Detection
Credible Intervals for Precision and Recall Based on a K -Fold Cross-Validated Beta Distribution
A Function Estimation Approach to Sequential Learning with Neural Networks
A Fast Fixed-Point Algorithm for Independent Component Analysis
Reduction from Cost-Sensitive Ordinal Ranking to Weighted Binary Classification
Parameter Convergence and Learning Curves for Neural Networks
Dynamics and Topographic Organization of Recursive Self-Organizing Maps
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications
Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks
Dynamic Signal Tracking in a Simple V1 Spiking Model
Instance-Specific Model Perturbation Improves Generalized Zero-Shot Learning
Autoregressive Point Processes as Latent State-Space Models: A Moment-Closure Approach to Fluctuations and Autocorrelations
Estimating a Separably Markov Random Field from Binary Observations
On the Relation of Slow Feature Analysis and Laplacian Eigenmaps
A Scalable Kernel-Based Semisupervised Metric Learning Algorithm with Out-of-Sample Generalization Ability
A Set Probability Technique for Detecting Relative Time Order Across Multiple Neurons
A Matrix Method for Optimizing a Neural Network
Magnification Control in Self-Organizing Maps and Neural Gas
Exponential Convergence of Delayed Dynamical Systems
Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2D and 3D Images
Quantifying Strength of Chaos in the Population Firing Rate of Neurons
Online Adaptive Decision Trees: Pattern Classification and Function Approximation
Nonlinear Extraction of Independent Components of Natural Images Using Radial Gaussianization
On the Capabilities of Higher-Order Neurons: A Radial Basis Function Approach
Constraint on the Number of Synaptic Inputs to a Visual Cortical Neuron Controls Receptive Field Formation
Insights from a Simple Expression for Linear Fisher Information in a Recurrently Connected Population of Spiking Neurons
Partial Orders of Similarity Differences Invariant Between EEG-Recorded Brain and Perceptual Representations of Language
Multiplicative Synaptic Normalization and a Nonlinear Hebb Rule Underlie a Neurotrophic Model of Competitive Synaptic Plasticity
Adaptive Synchronization of Activities in a Recurrent Network
Accelerating Nonnegative Matrix Factorization Algorithms Using Extrapolation
Bayesian Filtering in Spiking Neural Networks: Noise, Adaptation, and Multisensory Integration
Dynamic Model of Visual Recognition Predicts Neural Response Properties in the Visual Cortex
What Can a Neuron Learn with Spike-Timing-Dependent Plasticity?
Neural Circuits Trained with Standard Reinforcement Learning Can Accumulate Probabilistic Information during Decision Making
Understanding Memories of the Past in the Context of Different Complex Neural Network Architectures
Divergence-Based Vector Quantization
Neural Network Spectral Robustness under Perturbations of the Underlying Graph
Learning Virtual Equilibrium Trajectories for Control of a Robot Arm
On the Noise-Enhancing Ability of Stochastic Hodgkin-Huxley Neuron Systems
Fast Population Coding
Decoding Hidden Cognitive States From Behavior and Physiology Using a Bayesian Approach
Synchrony of Fast-Spiking Interneurons Interconnected by GABAergic and Electrical Synapses
Possible Roles of Spontaneous Waves and Dendritic Growth for Retinal Receptive Field Development
Analysis of the Interaction Between the Dendritic Conductance Density and Activated Area in Modulating alpha-Motoneuron EPSP: Statistical Computer Model
Probing Changes in Neural Interaction During Adaptation
Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms
A Global Optimum Approach for One-Layer Neural Networks
Why Does Large Batch Training Result in Poor Generalization? A Comprehensive Explanation and a Better Strategy from the Viewpoint of Stochastic Optimization
Stable Encoding of Finite-State Machines in Discrete-Time Recurrent Neural Nets with Sigmoid Units
Distortion of Neural Signals by Spike Coding
An in Silico, Biomarker-Based Method for the Evaluation of Virtual Neuropsychiatric Drug Effects
A Monte Carlo EM Approach for Partially Observable Diffusion Processes: Theory and Applications to Neural Networks
An Asymptotic Statistical Theory of Polynomial Kernel Methods
Rademacher Chaos Complexities for Learning the Kernel Problem
Regularized neural networks: some convergence rate results
Surface Interpolation in Three-Dimensional Structure-from-Motion Perception
Molecular Diffusion Model of Neurotransmitter Homeostasis Around Synapses Supporting Gradients
Reinforcement Learning in Sparse-Reward Environments With Hindsight Policy Gradients
Discriminant Pattern Recognition Using Transformation-Invariant Neurons
The Dynamics of Discrete-Time Computation, with Application to Recurrent Neural Networks and Finite State Machine Extraction
Four Types of Learning Curves
Distance Learning in Discriminative Vector Quantization
A theory of the visual motion coding in the primary visual cortex
Learning a Decision Boundary from Stochastic Examples: Incremental Algorithms with and without Queries
Exploring Trade-Offs in Spiking Neural Networks
A Semiparametric Bayesian Model for Detecting Synchrony Among Multiple Neurons
Bayesian Feature Selection with Strongly Regularizing Priors Maps to the Ising Model
Effect of Depth and Width on Local Minima in Deep Learning
Spike-Timing-Dependent Plasticity and Relevant Mutual Information Maximization
Synchrony and Complexity in State-Related EEG Networks: An Application of Spectral Graph Theory
Dynamic State and Parameter Estimation Applied to Neuromorphic Systems
Associative Learning and Active Inference
Adversarial Feature Alignment: Avoid Catastrophic Forgetting in Incremental Task Lifelong Learning
Spiking Elementary Motion Detector in Neuromorphic Systems
Bayesian Estimation of Stimulus Responses in Poisson Spike Trains
Influence of External Inputs and Asymmetry of Connections on Information-Geometric Measures Involving Up to Ten Neuronal Interactions
Jacobian Conditioning Analysis for Model Validation
A Tutorial on the Spectral Theory of Markov Chains
Generalization and Multirate Models of Motor Adaptation
Single-Snippet Analysis for Detection of Postspike Effects
Window-Based Example Selection in Learning Vector Quantization
Learning and generalization in radial basis function networks
Data Efficiency, Dimensionality Reduction, and the Generalized Symmetric Information Bottleneck
How the Brain Generates Movement
Edgeworth Approximation of Multivariate Differential Entropy
Validation of Voting Committees
Training a Support Vector Machine in the Primal
Separating Spike Count Correlation from Firing Rate Correlation