Computational Neuroscience: Publications
Read the latest papers published by our researchers.
Results
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Lyapunov spectrum of random neural networks
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From stuff to things: Responses of neurons in macaque V4 to textures and objects
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The Squealer: Sensification of model exploration and model misfit
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Similarity of Neural Network Representations in Superposition
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GEOPHYS: The Geometry of Physical Plausibility
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Learning a Maximum Entropy Model for Visual Textures using Diffusion
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Task-Induced Representational Invariances Depend on Learning Objective in Deep RL
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Diffusion models learn underlying trends in actomyosin networks and predict behavior at unseen filament turnover
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Two Speeds of Learning: A Representation-Readout Decomposition of Grokking and Double Descent
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Learning Normalized Energy Models for Linear Inverse Problems
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How Data Augmentation Shapes Neural Representations
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Tracking the Fidelity of Internal Neural Representations with Error-In-Variables Regression
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There Will Be a Scientific Theory of Deep Learning
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Modulating Cross-Modal Convergence with Single-Stimulus, Intra-Modal Dispersion
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Spectral Analysis of Representational Similarity with Limited Neurons
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Reproducibility and model-selection stability in connectome-constrained circuit modeling
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Partial Soft-Matching Distance for Neural Representational Comparison with Partial Unit Correspondence
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Quasi Monte Carlo methods enable extremely low-dimensional deep generative models
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Estimating Dimensionality of Neural Representations from Finite Samples
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Approximate posterior recalibration
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A Network of Biologically Inspired Rectified Spectral Units (ReSUs) Learns Hierarchical Features Without Error Backpropagation
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Linear Readout of Neural Manifolds with Continuous Variables
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Diagnosing Generalization Failures from Representational Geometry Markers
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Natural Image Statistics, Visual Representation, and Denoising
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The head-direction signal is generated by multiple attractor-like networks
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Emergent Manifold Separability during Reasoning in Large Language Models
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Learning a distance measure from the information-estimation geometry of data
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Months-long stability of the head-direction system
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Blind denoising diffusion models and the blessings of dimensionality
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Neural population geometry and optimal coding of tasks with shared latent structure
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Sparse input representations explain odor discrimination in complex, concentration-varying mixtures
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Neurons as Detectors of Coherent Sets in Sensory Dynamics
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Learning normalized image densities via dual score matching
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Scalable inference of functional neural connectivity at submillisecond timescales
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Disentangled representations via score-based variational autoencoders
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From labels to latents: revealing state-dependent hippocampal computations with Jump Latent Variable Model
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Comprehensive characterization of human color discrimination thresholds
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Open Data In Neurophysiology: Advancements, Solutions & Challenges
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A theory of initialisation’s impact on specialisation
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Modeling Neural Activity with Conditionally Linear Dynamical Systems
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Unconditional CNN denoisers contain sparse semantic representation of images
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Effective computations for hippocampal place cell phenomena in sparse untrained random networks
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Correcting Non-Uniform Milling in FIB-SEM Images with Unsupervised Cross-Plane Image-to-Image Translation
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End-to-end Topographic Auditory Models Replicate Signatures of Human Auditory Cortex
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Spatial Frequency Maps in Human Visual Cortex: A Replication and Extension
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Stochastic Process Inference Without Trajectories: A Probabilistic Approach
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Statistical mechanics of support vector regression
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Feature Learning beyond the Lazy-Rich Dichotomy: Insights from Representational Geometry