Toward a mechanistic understanding of inference in visual cortex and diffusion models | Paper Citation Record

Observation cf2ebc38-919b-490a-8497-6a78eba5acd9 · outbound

This paper cites Contour integration by the human visual system: evidence for a local “association field.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Contour integration by the human visual system: evidence for a local “association field

Reference 1

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This paper cites Robust and interpretable blind image denoising via bias-free convolutional neural networks.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Robust and interpretable blind image denoising via bias-free convolutional neural networks

Reference 2

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This paper cites Synaptic physiology of horizontal connections in the cat’s visual cortex,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Synaptic physiology of horizontal connections in the cat’s visual cortex,

Reference 3

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This paper cites The functional organization of local circuits in visual cortex: insights from the study of tree shrew striate cortex,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models The functional organization of local circuits in visual cortex: insights from the study of tree shrew striate cortex,

Reference 4

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This paper cites Learning horizontal connections in a sparse coding model of natural images,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Learning horizontal connections in a sparse coding model of natural images,

Reference 5

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This paper cites Hierarchical bayesian inference in the visual cortex,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Hierarchical bayesian inference in the visual cortex,

Reference 6

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This paper cites Neural variability and sampling-based proba- bilistic representations in the visual cortex,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Neural variability and sampling-based proba- bilistic representations in the visual cortex,

Reference 7

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This paper cites Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference,

Reference 8

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This paper cites Trace inference, curvature consistency, and curve detection,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Trace inference, curvature consistency, and curve detection,

Reference 9

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This paper cites Visual brain and visual perception: how does the cortex do perceptual grouping?,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Visual brain and visual perception: how does the cortex do perceptual grouping?,

Reference 10

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This paper cites A neural model of contour integration in the primary visual cortex,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models A neural model of contour integration in the primary visual cortex,

Reference 11

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This paper cites A detailed theory of thalamic and cortical microcircuits for predictive visual inference,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models A detailed theory of thalamic and cortical microcircuits for predictive visual inference,

Reference 12

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This paper cites Generative inference unifies feedback processing for learning and perception in natural and artificial vision,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Generative inference unifies feedback processing for learning and perception in natural and artificial vision,

Reference 13

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This paper cites A generative vision model that trains with high data efficiency and breaks text-based captchas,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models A generative vision model that trains with high data efficiency and breaks text-based captchas,

Reference 14

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This paper cites Emergence of simple-cell receptive field properties by learning a sparse code for natural images,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Emergence of simple-cell receptive field properties by learning a sparse code for natural images,

Reference 15

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This paper cites Sparse coding with an overcomplete basis set: A strategy employed by V1?,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Sparse coding with an overcomplete basis set: A strategy employed by V1?,

Reference 16

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Observation c87bbb8f-f696-4fe8-8e69-793a86d8b0e7 · outbound

This paper cites Relations between the statistics of natural images and the response properties of cortical cells,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Relations between the statistics of natural images and the response properties of cortical cells,

Reference 17

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This paper cites What is the goal of sensory coding?,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models What is the goal of sensory coding?,

Reference 18

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This paper cites What natural scene statistics can tell us about cortical representation,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models What natural scene statistics can tell us about cortical representation,

Reference 19

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This paper cites Modeling the joint statistics of images in the wavelet domain,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Modeling the joint statistics of images in the wavelet domain,

Reference 20

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This paper cites A parametric texture model based on joint statistics of complex wavelet coefficients,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models A parametric texture model based on joint statistics of complex wavelet coefficients,

Reference 21

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This paper cites Hyvärinen, J.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Hyvärinen, J

Reference 22

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This paper cites The nonlinear statistics of high-contrast patches in natural images,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models The nonlinear statistics of high-contrast patches in natural images,

Reference 23

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This paper cites On the local behavior of spaces of natural images,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models On the local behavior of spaces of natural images,

Reference 24

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This paper cites The sparse manifold transform,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models The sparse manifold transform,

Reference 25

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This paper cites Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning

Reference 26

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This paper cites Edge co-occurrence in natural images predicts contour grouping performance,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Edge co-occurrence in natural images predicts contour grouping performance,

Reference 27

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This paper cites On a common circle: natural scenes and gestalt rules,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models On a common circle: natural scenes and gestalt rules,

Reference 28

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This paper cites A fast iterative shrinkage-thresholding algorithm for linear inverse problems,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models A fast iterative shrinkage-thresholding algorithm for linear inverse problems,

Reference 29

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This paper cites Emergence of phase-and shift-invariant features by decomposition of natural images into independent feature subspaces,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Emergence of phase-and shift-invariant features by decomposition of natural images into independent feature subspaces,

Reference 30

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This paper cites Natural signal statistics and sensory gain control,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Natural signal statistics and sensory gain control,

Reference 31

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Topographic independent component analysis,

Reference 32

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Learning higher-order structures in natural images,

Reference 33

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Toward a mechanistic understanding of inference in visual cortex and diffusion models A hierarchical bayesian model for learning nonlinear statistical regularities in nonstationary natural signals,

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Learning image representations from the pixel level via hierar- chical sparse coding,

Reference 35

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Toward a mechanistic understanding of inference in visual cortex and diffusion models A hierarchical statistical model of natural images explains tuning properties in v2,

Reference 36

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Learning visual spatial pooling by strong pca dimension reduc- tion,

Reference 37

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Effect of top-down connections in hierarchical sparse coding,

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Subspace locally competi- tive algorithms,

Reference 39

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Group sparse coding with a laplacian scale mixture prior,

Reference 40

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Bilinear models of natural images,

Reference 41

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Topographic product models applied to natural scene statistics,

Reference 42

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Extracting and composing robust features with denoising autoencoders,

Reference 43

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Deep unsupervised learning using nonequilibrium thermodynamics,

Reference 44

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Neural empirical bayes,

Reference 45

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Denoising diffusion probabilistic models,

Reference 46

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Score-based generative modeling through stochastic differential equations,

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This paper cites Generalization in diffusion models arises from geometry-adaptive harmonic representations.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Generalization in diffusion models arises from geometry-adaptive harmonic representations

Reference 48

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Toward a mechanistic understanding of inference in visual cortex and diffusion models An analytic theory of creativity in convolutional diffusion models

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This paper cites Towards a Mechanistic Explanation of Diffusion Model Generalization.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Towards a Mechanistic Explanation of Diffusion Model Generalization

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Do Diffusion Models Learn Semantically Meaningful and Efficient Representations?

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This paper cites A fast iterative shrinkage-thresholding algorithm for linear inverse problems,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models A fast iterative shrinkage-thresholding algorithm for linear inverse problems,

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Unresolved cited work

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Generalization of back propagation to recurrent and higher order neural networks,

Reference 54

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Toward a mechanistic understanding of inference in visual cortex and diffusion models A learning rule for asynchronous perceptrons with feedback in a combinatorial environment,

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Reference 56

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Toward a mechanistic understanding of inference in visual cortex and diffusion models On training implicit models,

Reference 57

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This paper cites Implicit deep learning,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Implicit deep learning,

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Fixed point diffusion models,

Reference 59

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This paper cites Hierarchical Reasoning Model.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Hierarchical Reasoning Model

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This paper cites Jfb: Jacobian-free backpropagation for implicit networks,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Jfb: Jacobian-free backpropagation for implicit networks,

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This paper cites Independent component filters of natural images compared with simple cells in primary visual cortex,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Independent component filters of natural images compared with simple cells in primary visual cortex,

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Observation 8b9bd2a4-5bf6-4967-a790-070a95d14f77 · outbound

This paper cites Single-neuron perturbations reveal feature-specific competition in v1,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Single-neuron perturbations reveal feature-specific competition in v1,

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This paper cites Circuits and mechanisms for surround modulation in visual cortex,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Circuits and mechanisms for surround modulation in visual cortex,

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Toward a mechanistic understanding of inference in visual cortex and diffusion models U-Net: Convolutional Networks for Biomedical Image Segmentation

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Deep learning,

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Deep residual learning for image recognition,

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Visualizing and understanding convolutional networks,

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Deconvolutional networks,

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Residual Connections Encourage Iterative Inference

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This paper cites A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models.

Toward a mechanistic understanding of inference in visual cortex and diffusion models A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Odet (odel): Shortcutting the time and the length in diffusion and flow models for faster sampling,

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small

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This paper cites & batson, j.(2025). on the biology of a large language model,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models & batson, j.(2025). on the biology of a large language model,

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This paper cites Minimalistic unsupervised representation learning with the sparse manifold transform,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Minimalistic unsupervised representation learning with the sparse manifold transform,

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This paper cites Nonlinear dimensionality reduction by locally linear embedding,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Nonlinear dimensionality reduction by locally linear embedding,

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This paper cites A global geometric framework for nonlinear dimensionality reduction,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models A global geometric framework for nonlinear dimensionality reduction,

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This paper cites Diffusion Model's Generalization Can Be Characterized by Inductive Biases toward a Data-Dependent Ridge Manifold.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Diffusion Model's Generalization Can Be Characterized by Inductive Biases toward a Data-Dependent Ridge Manifold

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This paper cites What does the retina know about natural scenes?,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models What does the retina know about natural scenes?,

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This paper cites Efficient coding of natural images with a population of noisy linear-nonlinear neurons,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Efficient coding of natural images with a population of noisy linear-nonlinear neurons,

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This paper cites Elucidating the design space of diffusion-based generative models,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Elucidating the design space of diffusion-based generative models,

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This paper cites A fast proximal method for convolutional sparse coding,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models A fast proximal method for convolutional sparse coding,

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This paper cites Diffusion models beat gans on image synthesis,.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Diffusion models beat gans on image synthesis,

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Toward a mechanistic understanding of inference in visual cortex and diffusion models Unresolved cited work

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This paper cites The outer Σ clamps this expansion, isolating local geometric cross-talk by ensuring perturbations only spread to activated neurons.

Toward a mechanistic understanding of inference in visual cortex and diffusion models The outer Σ clamps this expansion, isolating local geometric cross-talk by ensuring perturbations only spread to activated neurons

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This paper cites Just as raising an adjacency matrix to the k-th power computes k-hop context-aware spread of activity defined by lateral connection.

Toward a mechanistic understanding of inference in visual cortex and diffusion models Just as raising an adjacency matrix to the k-th power computes k-hop context-aware spread of activity defined by lateral connection

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