OOIR: Observatory of International Research

Papers

(The TQCC of Neural Computation is 4. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-02-01 to 2025-02-01.)

Article	Citations
Dynamic Modeling of Spike Count Data With Conway-Maxwell Poisson Variability	98
Lateral Connections Improve Generalizability of Learning in a Simple Neural Network	93
On the Explainability of Graph Convolutional Network With GCN Tangent Kernel	82
Do Neural Networks for Segmentation Understand Insideness?	69
Conductance-Based Phenomenological Nonspiking Model: A Dimensionless and Simple Model That Reliably Predicts the Effects of Conductance Variations on Nonspiking Neuronal Dynamics	66
Gaussian Process Koopman Mode Decomposition	49
Categorical Perception: A Groundwork for Deep Learning	38
Toward a Biomimetic Neural Circuit Model of Sensory-Motor Processing	36
Formal Verification of Deep Brain Stimulation Controllers for Parkinson's Disease Treatment	32
NetPyNE Implementation and Scaling of the Potjans-Diesmann Cortical Microcircuit Model	31
Few-Shot Learning in Spiking Neural Networks by Multi-Timescale Optimization	31
Sensitivity of Sparse Codes to Image Distortions	27
Attention in a Family of Boltzmann Machines Emerging From Modern Hopfield Networks	27
Training Deep Convolutional Spiking Neural Networks With Spike Probabilistic Global Pooling	26
Multimodal and Multifactor Branching Time Active Inference	21
The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion	21
Deep Nonnegative Matrix Factorization With Beta Divergences	20
On an Interpretation of ResNets via Gate-Network Control	20
Synaptic Information Storage Capacity Measured With Information Theory	20
Deconstructing Deep Active Inference: A Contrarian Information Gatherer	19
Learning in Volatile Environments With the Bayes Factor Surprise	18
Classification of Autism Spectrum Disorder From EEG-Based Functional Brain Connectivity Analysis	18
Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies	16
On Neural Associative Memory Structures: Storage and Retrieval of Sequences in a Chain of Tournaments	15
Neuromorphic Engineering: In Memory of Misha Mahowald	14

Stability Conditions of Bicomplex-Valued Hopfield Neural Networks	14
Approximating Nonlinear Functions With Latent Boundaries in Low-Rank Excitatory-Inhibitory Spiking Networks	13
Linear Codes for Hyperdimensional Computing	12
Restricted Boltzmann Machines as Models of Interacting Variables	12
Information Geometrically Generalized Covariate Shift Adaptation	12
The Tensor Brain: A Unified Theory of Perception, Memory, and Semantic Decoding	12
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting	12
On Neural Network Kernels and the Storage Capacity Problem	12
Parameter Estimation in Multiple Dynamic Synaptic Coupling Model Using Bayesian Point Process State-Space Modeling Framework	11
Differential Geometry Methods for Constructing Manifold-Targeted Recurrent Neural Networks	11
From Univariate to Multivariate Coupling Between Continuous Signals and Point Processes: A Mathematical Framework	11
Enhanced Equivalence Projective Simulation: A Framework for Modeling Formation of Stimulus Equivalence Classes	11
Distributed Phase Oscillatory Excitation Efficiently Produces Attractors Using Spike-Timing-Dependent Plasticity	11
Obtaining Lower Query Complexities Through Lightweight Zeroth-Order Proximal Gradient Algorithms	10
Efficient Decoding of Large-Scale Neural Population Responses With Gaussian-Process Multiclass Regression	10
A Biologically Plausible Neural Network for Multichannel Canonical Correlation Analysis	10
A Simple Model of Nonspiking Neurons	9
Orthogonal Gated Recurrent Unit With Neumann-Cayley Transformation	8
Manifold Gaussian Variational Bayes on the Precision Matrix	8
A Fast Algorithm for All-Pairs-Shortest-Paths Suitable for Neural Networks	8
Mean-Field Approximations With Adaptive Coupling for Networks With Spike-Timing-Dependent Plasticity	8
Nonlinear Decoding of Natural Images From Large-Scale Primate Retinal Ganglion Recordings	8
Efficient Hyperdimensional Computing With Spiking Phasors	8
From Pavlov Conditioning to Hebb Learning	8
Implicit Regularization and Momentum Algorithms in Nonlinearly Parameterized Adaptive Control and Prediction	7
A Generalized Framework of Multifidelity Max-Value Entropy Search Through Joint Entropy	7
Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures	7
On Suspicious Coincidences and Pointwise Mutual Information	7
Online Mental Fatigue Monitoring via Indirect Brain Dynamics Evaluation	6
Relating Human Error–Based Learning to Modern Deep RL Algorithms	6
Bounded Rational Decision Networks With Belief Propagation	6
Large Language Models and the Reverse Turing Test	6
A Computational Study on Synaptic Plasticity Regulation and Information Processing in Neuron-Astrocyte Networks	6
Errata to “A Tutorial on the Spectral Theory of Markov Chains” by Eddie Seabrook and Laurenz Wiskott (Neural Computation, November 2023, Vol. 35, No. 11, pp. 1713–1796, https://doi.org/10.1162/	6
A Dynamic Neural Field Model of Multimodal Merging: Application to the Ventriloquist Effect	6
Probing the Relationship Between Latent Linear Dynamical Systems and Low-Rank Recurrent Neural Network Models	6
Toward a Free-Response Paradigm of Decision-Making in Spiking Neural Networks	6
Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition	5
Cooperativity, Information Gain, and Energy Cost During Early LTP in Dendritic Spines	5
Inference on the Macroscopic Dynamics of Spiking Neurons	5
Uncovering Dynamical Equations of Stochastic Decision Models Using Data-Driven SINDy Algorithm	5
Efficient Decoding of Compositional Structure in Holistic Representations	5
Replay as a Basis for Backpropagation Through Time in the Brain	5
Fine Granularity Is Critical for Intelligent Neural Network Pruning	5
Learning the Synaptic and Intrinsic Membrane Dynamics Underlying Working Memory in Spiking Neural Network Models	5
On PDE Characterization of Smooth Hierarchical Functions Computed by Neural Networks	5
A Neurodynamic Model of Saliency Prediction in V1	5
Spiking Neural Network Pressure Sensor	5
Toward a Kernel-Based Uncertainty Decomposition Framework for Data and Models	5
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications	4

Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses	4
Modeling the Role of Contour Integration in Visual Inference	4
Model Based or Model Free? Comparing Adaptive Methods for Estimating Thresholds in Neuroscience	4
Lifelong Classification in Open World With Limited Storage Requirements	4
Object-Centric Scene Representations Using Active Inference	4
Realizing Synthetic Active Inference Agents, Part II: Variational Message Updates	4
Principal Component Analysis for Gaussian Process Posteriors	4
Progressive Interpretation Synthesis: Interpreting Task Solving by Quantifying Previously Used and Unused Information	4
Direction Matters: On Influence-Preserving Graph Summarization and Max-Cut Principle for Directed Graphs	4
Gradual Domain Adaptation via Normalizing Flows	4
Unsupervised Learning of Temporal Abstractions With Slot-Based Transformers	4
Single Circuit in V1 Capable of Switching Contexts During Movement Using an Inhibitory Population as a Switch	4
A Double-Layer Multi-Resolution Classification Model for Decoding Spatiotemporal Patterns of Spikes With Small Sample Size	4
Mathematical Modeling of PI3K/Akt Pathway in Microglia	4
Body Mechanics, Optimality, and Sensory Feedback in the Human Control of Complex Objects	4
Permitted Sets and Convex Coding in Nonthreshold Linear Networks	4
A Mean Field to Capture Asynchronous Irregular Dynamics of Conductance-Based Networks of Adaptive Quadratic Integrate-and-Fire Neuron Models	4