yusuke1997/dblp-id-title huggingface dataset:
Collective Stability of Networks of Winner-Take-All Circuits
Detecting and Estimating Signals over Noisy and Unreliable Synapses: Information-Theoretic Analysis
Minimizing Binding Errors Using Learned Conjunctive Features
Sparse Coding via Thresholding and Local Competition in Neural Circuits
Efficient Markov Chain Monte Carlo Methods for Decoding Neural Spike Trains
How Convolutional Neural Network Architecture Biases Learned Opponency and Color Tuning
Dynamics of Gamma Bursts in Local Field Potentials
A Spike-Timing-Based Integrated Model for Pattern Recognition
Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning
Computing With Self-Excitatory Cliques: A Model and an Application to Hyperacuity-Scale Computation in Visual Cortex
A Network Model of Perceptual Suppression Induced by Transcranial Magnetic Stimulation
Learning Finite State Machines With Self-Clustering Recurrent Networks
Predictive Coding in Area V4: Dynamic Shape Discrimination under Partial Occlusion
Extracting Rules from Neural Networks by Pruning and Hidden-Unit Splitting
Democratic Integration: Self-Organized Integration of Adaptive Cues
A Fast Algorithm for Learning Overcomplete Dictionary for Sparse Representation Based on Proximal Operators
On PDE Characterization of Smooth Hierarchical Functions Computed by Neural Networks
Determination of Response Latency and Its Application to Normalization of Cross-Correlation Measures
Effective Neuronal Learning with Ineffective Hebbian Learning Rules
Online Ranking by Projecting
Conductance-Based Integrate and Fire Models
A Simple Hebbian/Anti-Hebbian Network Learns the Sparse, Independent Components of Natural Images
Active Predictive Coding: A Unifying Neural Model for Active Perception, Compositional Learning, and Hierarchical Planning
Representing Objects, Relations, and Sequences
Population Vectors Can Provide Near Optimal Integration of Information
Towards A Biophysically Plausible Bidirectional Hebbian Rule
Information-Theoretic Representation Learning for Positive-Unlabeled Classification
The Dynamic Neural Filter: A Binary Model of Spatiotemporal Coding
Learning in Volatile Environments With the Bayes Factor Surprise
A Single Hidden Layer Feedforward Network with Only One Neuron in the Hidden Layer Can Approximate Any Univariate Function
Information Transmission Using Non-Poisson Regular Firing
Deep Clustering With a Constraint for Topological Invariance Based on Symmetric InfoNCE
Duality Between Learning Machines: A Bridge Between Supervised and Unsupervised Learning
Fusing Foveal Fixations Using Linear Retinal Transformations and Bayesian Experimental Design
Gamma Oscillations in a Nonlinear Regime: A Minimal Model Approach Using Heterogeneous Integrate-and-Fire Networks
Real-Time Computation at the Edge of Chaos in Recurrent Neural Networks
Generalization Analysis of Transformers in Distribution Regression
General Poisson Exact Breakdown of the Mutual Information to Study the Role of Correlations in Populations of Neurons
A Causal Perspective on the Analysis of Signal and Noise Correlations and Their Role in Population Coding
Justifying and Generalizing Contrastive Divergence
Dependence of Neuronal Correlations on Filter Characteristics and Marginal Spike Train Statistics
Predicting the Future With a Scale-Invariant Temporal Memory for the Past
On the Emergence of Rules in Neural Networks
On Resolving Simultaneous Congruences Using Belief Propagation
Decreasing the Size of the Restricted Boltzmann Machine
Discriminant Component Pruning: Regularization and Interpretation of Multi-Layered Back-Propagation Networks
Efficient Decoding of Compositional Structure in Holistic Representations
Per-Round Knapsack-Constrained Linear Submodular Bandits
Training Feedforward Neural Networks with Gain Constraints
Derivation of Human Chromatic Discrimination Ability from an Information-Theoretical Notion of Distance in Color Space
Online Variational Inference for State-Space Models with Point-Process Observations
Learning Active Fusion of Multiple Experts' Decisions: An Attention-Based Approach
Conductance-Based Adaptive Exponential Integrate-and-Fire Model
Linear Response Algorithms for Approximate Inference in Graphical Models
Analytical Integrate-and-Fire Neuron Models with Conductance-Based Dynamics and Realistic Postsynaptic Potential Time Course for Event-Driven Simulation Strategies
Reclassification as Supervised Clustering
Sensory Metrics of Neuromechanical Trust
Manifold Gaussian Variational Bayes on the Precision Matrix
Online Learning with (Multiple) Kernels: A Review
A Biologically Supported Error-Correcting Learning Rule
Skip-Connected Self-Recurrent Spiking Neural Networks With Joint Intrinsic Parameter and Synaptic Weight Training
Evolving Network Model That Almost Regenerates Epileptic Data
The Shape of Phase-Resetting Curves in Oscillators with a Saddle Node on an Invariant Circle Bifurcation
Quantitative analysis of electrotonic structure and membrane properties of NMDA-activated lamprey spinal neurons
Dynamics of Feature Categorization
A Neural Circuit for Robust Time-to-Contact Estimation Based on Primate MST
On the Synthesis of Brain-State-in-a-Box Neural Models with Application to Associative Memory
Universal Approximation of Multiple Nonlinear Operators by Neural Networks
The Combinatorics of Neurite Self-Avoidance
Clusterless Decoding of Position from Multiunit Activity Using a Marked Point Process Filter
Sensitivity of Synaptic Plasticity to the Ca 2+ Permeability of NMDA Channels: A Model of Long-Term Potentiation in Hippocampal Neurons
A Geometrical Analysis of Global Stability in Trained Feedback Networks
Limitations of Proposed Signatures of Bayesian Confidence
Joint Entropy Maximization in Kernel-Based Topographic Maps
Predictive Approaches for Choosing Hyperparameters in Gaussian Processes
Minimum Description Length, Regularization, and Multimodal Data
Computing Sparse Representations of Multidimensional Signals Using Kronecker Bases
Complexity Pursuit: Separating Interesting Components from Time Series
A Smoothing Regularizer for Feedforward and Recurrent Neural Networks
A Penalty-Function Approach for Pruning Feedforward Neural Networks
Statistical Approach to Shape from Shading: Reconstruction of Three-Dimensional Face Surfaces from Single Two-Dimensional Images
The Role of Extracellular Conductivity Profiles in Compartmental Models for Neurons: Particulars for Layer 5 Pyramidal Cells
Psychophysically Tuned Divisive Normalization Approximately Factorizes the PDF of Natural Images
Model Reductions for Inference: Generality of Pairwise, Binary, and Planar Factor Graphs
Modeling Higher-Order Interactions in Sparse and Heavy-Tailed Neural Population Activity
Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives
Effective Dimensionality Reduction for Visualizing Neural Dynamics by Laplacian Eigenmaps
Differential Filtering of Two Presynaptic Depression Mechanisms
Dual Information Representation with Stable Firing Rates and Chaotic Spatiotemporal Spike Patterns in a Neural Network Model
Learning by Assertion: Two Methods for Calibrating a Linear Visual System
Distinguishing Causal Interactions in Neural Populations
A Stochastic Self-Organizing Map for Proximity Data
Issues in Bayesian Analysis of Neural Network Models
Self-organization as an iterative kernel smoothing process
Efficient Adaptive Learning for Classification Tasks with Binary Units
A Theoretical Analysis of the Influence of Fixational Instability on the Development of Thalamocortical Connectivity
Some Generalized Sufficient Convergence Criteria for Nonlinear Continuous Neural Networks
Refined Spectral Clustering via Embedded Label Propagation
Neurons Tune to the Earliest Spikes Through STDP
A Resource-Allocating Network for Function Interpolation
Learning in Associative Networks Through Pavlovian Dynamics
A Comparative Study of Feature-Salience Ranking Techniques
Interspike Interval Correlations, Memory, Adaptation, and Refractoriness in a Leaky Integrate-and-Fire Model with Threshold Fatigue
Retrieval Properties of a Hopfield Model with Random Asymmetric Interactions
Partial BFGS Update and Efficient Step-Length Calculation for Three-Layer Neural Networks
A Novel Neural Network for a Class of Convex Quadratic Minimax Problems
An HMM/MLP Architecture for Sequence Recognition
Robustness to Transformations Across Categories: Is Robustness Driven by Invariant Neural Representations?
Radius Margin Bounds for Support Vector Machines with the RBF Kernel
Trading Variance Reduction with Unbiasedness: The Regularized Subspace Information Criterion for Robust Model Selection in Kernel Regression
Finding the Event Structure of Neuronal Spike Trains
Convergent Decomposition Techniques for Training RBF Neural Networks
A Constrained EM Algorithm for Independent Component Analysis
A New Approach to Spatial Covariance Modeling of Functional Brain Imaging Data: Ordinal Trend Analysis
Facial Attractiveness: Beauty and the Machine
Bayesian k -Means as a "Maximization-Expectation" Algorithm
Formation of Direction Selectivity in Natural Scene Environments
Rapid Convergence to Feature Layer Correspondences
On the Geometry of Feedforward Neural Network Error Surfaces
Adaptive Improved Natural Gradient Algorithm for Blind Source Separation
Locality of Global Stochastic Interaction in Directed Acyclic Networks
Towards Optimally Distributed Computation
Integrating Flexible Normalization into Midlevel Representations of Deep Convolutional Neural Networks
Adaptive Gaussian Process Approximation for Bayesian Inference with Expensive Likelihood Functions
Expectation Propagation with Factorizing Distributions: A Gaussian Approximation and Performance Results for Simple Models
Topology Learning Solved by Extended Objects: A Neural Network Model
Simple Neural-Like P Systems for Maximal Independent Set Selection
Concentration Tuning Mediated by Spare Receptor Capacity in Olfactory Sensory Neurons: A Theoretical Study
Deeply Felt Affect: The Emergence of Valence in Deep Active Inference
Neural Network Process Models Based on Linear Model Structures
Active Learning Using Hint Information
Generalization in Interactive Networks: The Benefits of Inhibitory Competition and Hebbian Learning
Variational Learning for Switching State-Space Models
Diffusion Approximations for the Constant Learning Rate Backpropagation Algorithm and Resistance to Local Minima
Importance of the Cutoff Value in the Quadratic Adaptive Integrate-and-Fire Model
Orientation Histogram-Based Center-Surround Interaction: An Integration Approach for Contour Detection
Almost Linear VC-Dimension Bounds for Piecewise Polynomial Networks
Chaotic Pattern Alternations Can Reproduce Properties of Dominance Durations in Multistable Perception
Refined Generalization Bounds of Gradient Learning over Reproducing Kernel Hilbert Spaces
A Simple Neural Network Exhibiting Selective Activation of Neuronal Ensemblies: From Winner-Take-All to Winners-Share-All
Spontaneous Motion on Two-Dimensional Continuous Attractors
Analysis of Neuron Models with Dynamically Regulated Conductances
Stochastic Single Neurons
Coding of Time-Varying Signals in Spike Trains of Integrate-and-Fire Neurons with Random Threshold
Synaptic Scaling Improves the Stability of Neural Mass Models Capable of Simulating Brain Plasticity
Improving the Generalization Properties of Radial Basis Function Neural Networks
Sample-Spacings-Based Density and Entropy Estimators for Spherically Invariant Multidimensional Data
Winner-Relaxing Self-Organizing Maps
Minimal Feedforward Parity Networks Using Threshold Gates
Bayesian Regularization and Pruning Using a Laplace Prior
Characterizing Brain Connectivity From Human Electrocorticography Recordings With Unobserved Inputs During Epileptic Seizures
Dimension Reduction by Local Principal Component Analysis
The Neural Representation of Time: An Information-Theoretic Perspective
Competitive STDP-Based Spike Pattern Learning
Local Feedback Multilayered Networks
An Efficient Method for Computing Synaptic Conductances Based on a Kinetic Model of Receptor Binding
Images, Frames, and Connectionist Hierarchies
The Berkeley Wavelet Transform: A Biologically Inspired Orthogonal Wavelet Transform
Simple Modification of Oja Rule Limits L 1 -Norm of Weight Vector and Leads to Sparse Connectivity
Traveling Waves of Excitation in Neural Field Models: Equivalence of Rate Descriptions and Integrate-and-Fire Dynamics
Robustness of Connectionist Swimming Controllers Against Random Variation in Neural Connections
Deconstructing Odorant Identity via Primacy in Dual Networks
Optimal Quadratic Binding for Relational Reasoning in Vector Symbolic Neural Architectures
Deconstructing Deep Active Inference: A Contrarian Information Gatherer
Modeling Orientation Discrimination at Multiple Reference Orientations with a Neural Network
Learning Curves for Gaussian Process Regression: Approximations and Bounds
Bayesian Analysis of Mixtures of Factor Analyzers
Fast Generalized Cross-Validation Algorithm for Sparse Model Learning
Indefinite Proximity Learning: A Review
A Note on Lewicki-Sejnowski Gradient for Learning Overcomplete Representations
Recurrent Neural Network for Computing Outer Inverse
Spiking Neural P Systems with a Generalized Use of Rules
Predictions of the Spontaneous Symmetry-Breaking Theory for Visual Code Completeness and Spatial Scaling in Single-Cell Learning Rules
Parameter Estimation for alpha-GMM Based on Maximum Likelihood Criterion
Adaptive Integration in the Visual Cortex by Depressing Recurrent Cortical Circuits
Category Learning Through Multi-Modality Sensing
Stimulus-Dependent Assembly Formation of Oscillatory Responses: III. Learning
Three-Dimensional Object Recognition Using an Unsupervised BCM Network: The Usefulness of Distinguishing Features
Identification of Stable Spike-Timing-Dependent Plasticity from Spiking Activity with Generalized Multilinear Modeling
Wide-Band Information Transmission at the Calyx of Held
Correlation and Independence in the Neural Code
Fast Estimation of Approximate Matrix Ranks Using Spectral Densities
Simultaneous Rate-Synchrony Codes in Populations of Spiking Neurons
Facilitation of Neuronal Responses by Intrinsic Default Mode Network Activity
A Neurocomputational Model for Cocaine Addiction
Theory of Input Spike Auto- and Cross-Correlations and Their Effect on the Response of Spiking Neurons
Chance-Constrained Active Inference
Optimizing Time Histograms for Non-Poissonian Spike Trains
Efficient Neural Codes That Minimize L p Reconstruction Error
Mutual Inhibition with Few Inhibitory Cells via Nonlinear Inhibitory Synaptic Interaction
Model-Based Decoding, Information Estimation, and Change-Point Detection Techniques for Multineuron Spike Trains
Learning Nonregular Languages: A Comparison of Simple Recurrent Networks and LSTM
Model-Free Robust Optimal Feedback Mechanisms of Biological Motor Control
A Statistical Framework to Infer Delay and Direction of Information Flow from Measurements of Complex Systems
Broken Symmetries in a Location-Invariant Word Recognition Network
An Extended EM Algorithm for Joint Feature Extraction and Classification in Brain-Computer Interfaces
An Analog Memory Circuit for Spiking Silicon Neurons
Self-Regulation Mechanism of Temporally Asymmetric Hebbian Plasticity
Top-Down Priors Disambiguate Target and Distractor Features in Simulated Covert Visual Search
Seeing White: Qualia in the Context of Decoding Population Codes
The Effect of Noise on a Class of Energy-Based Learning Rules
A Unified Approach to Building and Controlling Spiking Attractor Networks
Determination and the No-Free-Lunch Paradox
Associative Learning of an Unnormalized Successor Representation
Dynamic Cell Structure Learns Perfectly Topology Preserving Map
Applications of Recurrent Neural Networks in Environmental Factor Forecasting: A Review
The Dynamics of Integrate-and-Fire: Mean Versus Variance Modulations and Dependence on Baseline Parameters
A Model Circuit for Cortical Temporal Low-Pass Filtering
Can Grid Cell Ensembles Represent Multiple Spaces?
Sufficient Dimension Reduction via Squared-Loss Mutual Information Estimation
Noise in Integrate-and-Fire Neurons: From Stochastic Input to Escape Rates
Linear Constraints on Weight Representation for Generalized Learning of Multilayer Networks
Replay in Deep Learning: Current Approaches and Missing Biological Elements
A Temporal Stability Approach to Position and Attention-Shift-Invariant Recognition
A modular and hybrid connectionist system for speaker identification
Dynamical Constraints on Using Precise Spike Timing to Compute in Recurrent Cortical Networks
Positive Neural Networks in Discrete Time Implement Monotone-Regular Behaviors
Integrator or Coincidence Detector: A Novel Measure Based on the Discrete Reverse Correlation to Determine a Neuron's Operational Mode
Understanding Parkinsonian Handwriting Through a Computational Model of Basal Ganglia
Functionally Equivalent Feedforward Neural Networks
Choice and Value Flexibility Jointly Contribute to the Capacity of a Subsampled Quadratic Classifier
Learning Slowness in a Sparse Model of Invariant Feature Detection
The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation Models
Correlation Between Eigenvalue Spectra and Dynamics of Neural Networks
Adaptive Method of Realizing Natural Gradient Learning for Multilayer Perceptrons
Unsupervised Domain Adaptation for Extra Features in the Target Domain Using Optimal Transport
On the Use of Dynamic Bayesian Networks in Reconstructing Functional Neuronal Networks from Spike Train Ensembles
State-Dependent Computation Using Coupled Recurrent Networks
Computation with Spikes in a Winner-Take-All Network
Semistability of Steepest Descent with Momentum for Quadratic Functions
Neural Networks for Functional Approximation and System Identification
A Novel Generic Hebbian Ordering-Based Fuzzy Rule Base Reduction Approach to Mamdani Neuro-Fuzzy System
Slow Feature Analysis: A Theoretical Analysis of Optimal Free Responses
The VC Dimension and Pseudodimension of Two-Layer Neural Networks with Discrete Inputs
Sequential Monte Carlo Point-Process Estimation of Kinematics from Neural Spiking Activity for Brain-Machine Interfaces
Hexagonal Grid Fields Optimally Encode Transitions in Spatiotemporal Sequences
A Neural Network Model of Inhibitory Information Processing in Aplysia
Frequency Selectivity Emerging from Spike-Timing-Dependent Plasticity
Multiperiodicity and Exponential Attractivity Evoked by Periodic External Inputs in Delayed Cellular Neural Networks
Approximating Nonlinear Functions With Latent Boundaries in Low-Rank Excitatory-Inhibitory Spiking Networks
Spike-Timing Error Backpropagation in Theta Neuron Networks
Activation Functions, Computational Goals and Learning Rules for Local Processors with Contextual Guidance
A Novel Recurrent Neural Network with Finite-Time Convergence for Linear Programming
Improving the Incoherence of a Learned Dictionary via Rank Shrinkage
Extracting Number-Selective Responses from Coherent Oscillations in a Computer Model
Hebbian Self-Organizing Integrate-and-Fire Networks for Data Clustering
Quantifying Neurotransmission Reliability Through Metrics-Based Information Analysis
Hints and the VC Dimension
Anti-Predictable Sequences: Harder to Predict Than Random Sequences
A Locally Optimal Algorithm for Estimating a Generating Partition from an Observed Time Series and Its Application to Anomaly Detection
Toward a Multisubject Analysis of Neural Connectivity
Stable Propagation of Activity Pulses in Populations of Spiking Neurons
Electrical Coupling Promotes Fidelity of Responses in the Networks of Model Neurons
The Computational Exploration of Visual Word Recognition in a Split Model
Local and Global Optimization Algorithms for Generalized Learning Automata
Mixture of Experts Classification Using a Hierarchical Mixture Model
A Study on Neural Learning on Manifold Foliations: The Case of the Lie Group SU (3)
Is There Something Out There? Inferring Space from Sensorimotor Dependencies
Adaptive Mixtures of Local Experts
Toward Generalized Entropic Sparsification for Convolutional Neural Networks
A Geometric Newton Method for Oja's Vector Field
Temporally Asymmetric Learning Supports Sequence Processing in Multi-Winner Self-Organizing Maps
Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON
Avoiding Optimal Mean ℓ 2, 1 -Norm Maximization-Based Robust PCA for Reconstruction
State-Space Models: From the EM Algorithm to a Gradient Approach
Precise Capacity Analysis in Binary Networks with Multiple Coding Level Inputs
A Population Density Approach That Facilitates Large-Scale Modeling of Neural Networks: Extension to Slow Inhibitory Synapses
Shapley Homology: Topological Analysis of Sample Influence for Neural Networks
Computation of Madalines' Sensitivity to Input and Weight Perturbations
Online Learning from Finite Training Sets and Robustness to Input Bias
Online Direct Density-Ratio Estimation Applied to Inlier-Based Outlier Detection
A Nonparametric Clustering Algorithm with a Quantile-Based Likelihood Estimator
Motion Contrast Classification Is a Linearly Nonseparable Problem
A Theoretical and Experimental Account of n -Tuple Classifier Performance
Current Source Density Reconstruction from Incomplete Data
Impact of Correlated Neural Activity on Decision-Making Performance
Axonal Processes and Neural Plasticity: A Reply
A Kernel Embedding-Based Approach for Nonstationary Causal Model Inference
Decoding Movement Trajectories Through a T-Maze Using Point Process Filters Applied to Place Field Data from Rat Hippocampal Region CA1
Sequential Learning in the Dense Associative Memory
Hierarchical Mixtures of Experts and the EM Algorithm
Context-Sensitive Processing in a Model Neocortical Pyramidal Cell With Two Sites of Input Integration
Modeling Sensorimotor Learning with Linear Dynamical Systems
Algorithmic Stability and Sanity-Check Bounds for Leave-One-Out Cross-Validation
Enhanced Gradient for Training Restricted Boltzmann Machines
Two-State Membrane Potential Fluctuations Driven by Weak Pairwise Correlations
Convergence and Ordering of Kohonen's Batch Map
The Limits of Counting Accuracy in Distributed Neural Representations
Improved Generative Semisupervised Learning Based on Finely Grained Component-Conditional Class Labeling
From Function to Implementation: Exploring Degeneracy in Evolved Artificial Agents
Online Model Selection Based on the Variational Bayes
Analytical Calculation of Errors in Time and Value Perception Due to a Subjective Time Accumulator: A Mechanistic Model and the Generation of Weber's Law
How Are Lateral Chromatic Interactions Computed from Cone Signals?
Parallel Neural Multiprocessing with Gamma Frequency Latencies
Decomposition Methods for Linear Support Vector Machines
Bayesian Brains and the Rényi Divergence
Computing Confidence Intervals for Point Process Models
Rate and Synchrony in Feedforward Networks of Coincidence Detectors: Analytical Solution
Modeling the Combination of Motion, Stereo, and Vergence Angle Cues to Visual Depth
Synchronization of the Neural Response to Noisy Periodic Synaptic Input
Equivalence of a Sprouting-And-Retraction Model and Correlation-Based Plasticity Models of Neural Development
The Cocktail Party Problem
Differences in Spiking Patterns Among Cortical Neurons
Active Inference, Evidence Accumulation, and the Urn Task
Anatomical Constraints on Lateral Competition in Columnar Cortical Architectures
On Decoding Grid Cell Population Codes Using Approximate Belief Propagation
Average-Case Learning Curves for Radial Basis Function Networks
A Mobile Robot that Learns its Place
An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity
Spatiotemporal Connectionist Networks: A Taxonomy and Review
Parallel Hopfield Networks
Diplomats' Mystery Illness and Pulsed Radiofrequency/Microwave Radiation
Neural Field Model of Receptive Field Restructuring in Primary Visual Cortex
Information Geometry of U-Boost and Bregman Divergence
Working Memory Networks for Learning Temporal Order with Application to Three-Dimensional Visual Object Recognition
Dynamic Consolidation for Continual Learning