Computational Neuroscience: Publications
Read the latest papers published by our researchers.
Results
-
Perpetual step-like restructuring of hippocampal circuit dynamics
-
Mapping models of V1 and V2 selectivity with local spectral reverse correlation
-
Fixational eye movements enhance the precision of visual information transmitted by the primate retina
-
Natural Image Densities: Learning, Understanding and Utilizing
-
Visual Temporal Prediction: Representation, Estimation, and Modeling
-
Geometric changes in monkey V4 and IT neural responses during visual category learning
-
Tensor Decomposition Meets RKHS: Efficient Algorithms for Smooth and Misaligned Data
-
Neuronal and behavioral responses to naturalistic texture images in macaque monkeys
-
Context-invariant beliefs are supported by dynamic reconfiguration of single unit functional connectivity in prefrontal cortex of male macaques
-
The neuron as a direct data-driven controller
-
Privileged representational axes in biological and artificial neural networks
-
Disparate nonlinear neural dynamics measured with different techniques in macaque and human V1
-
Layerwise complexity-matched learning yields an improved model of cortical area {V2}
-
HybridBNN: Joint Training of Deterministic and Stochastic Layers in Bayesian Neural Nets
-
Optimal compressed sensing for image reconstruction with diffusion probabilistic models
-
Versatile multiple object tracking in sparse 2D/3D videos via deformable image registration
-
A unified framework for perceived magnitude and discriminability of sensory stimuli
-
Estimating Shape Distances on Neural Representations with Limited Samples
-
Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations
-
Disentangling Recurrent Neural Dynamics with Stochastic Representational Geometry
-
On the universality of neural encodings in CNNs
-
Neural Manifold Capacity Captures Representation Geometry, Correlations, and Task-Efficiency Across Species and Behaviors
-
Neuronal Temporal Filters as Normal Mode Extractors
-
Complex priors and flexible inference in recurrent circuits with dendritic nonlinearities
-
Generalization in diffusion models arises from geometry-adaptive harmonic representations
-
Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds
-
Comparing neural models using their perceptual discriminability predictions
-
Efficient coding of natural images using maximum manifold capacity representations
-
Adaptive whitening with fast gain modulation and slow synaptic plasticity
-
A polar prediction model for learning to represent visual transformations
-
Targeted V1 comodulation supports task-adaptive sensory decisions
-
Spatiotemporal Clustering with Neyman-Scott Processes via Connections to Bayesian Nonparametric Mixture Models
-
Foveated metamers of the early visual system
-
Neural network adaptive coding efficiency and stochastic representational geometry
-
Normative framework for deriving neural networks with multi-compartmental neurons and non-Hebbian plasticity
-
Unlocking the Potential of Similarity Matching: Scalability, Supervision and Pre-training
-
Learning multi-scale local conditional probability models of images
-
Spatial frequency selectivity in macaque LGN and V1
-
Catalyzing next-generation [Artificial Intelligence} through {NeuroAI}
-
Catalyzing next-generation Artificial Intelligence through NeuroAI
-
Polar prediction of natural videos
-
Coordinated drift of receptive fields in Hebbian/anti-Hebbian network models during noisy representation learning
-
Fine-tuning hierarchical circuits through learned stochastic co-modulation
-
Maximum a posteriori natural scenes reconstruction from retinal ganglion cells with deep denoiser priors
-
Normative theories of synaptic plasticity for representation and perceptual discrimination
-
Neural Circuits for Dynamics-Based Segmentation of Time Serie
-
Deep denoising for scientific discovery: A case study in electron microscopy
-
Robust and interpretable denoising via deep learning