Paper Citation Record · LEDGER

Convolutional Vision Transformer for Cosmology Parameter Inference

As of 13 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 2 inbound Pith citation observations for arXiv:2411.14392.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.14392 v2

Coverage vector

measured 27 of 27 reference resolution

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Source: arxiv_reference, observed 2026-07-04T11:59:50.359106Z

Reference resolution

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Outbound references

Observation d750877b-4799-4027-9116-9fc00c05b689 · outbound

This paper cites Bayesian field-level inference of primordial non-Gaussianity using next-generation galaxy surveys.

Convolutional Vision Transformer for Cosmology Parameter Inference Bayesian field-level inference of primordial non-Gaussianity using next-generation galaxy surveys

Reference 1

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Observation 2d2d416c-1699-44e6-b405-7bfcebb3595f · outbound

This paper cites Better plain ViT baselines for ImageNet-1k.

Convolutional Vision Transformer for Cosmology Parameter Inference Better plain ViT baselines for ImageNet-1k

Reference 2

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Observation fe17bf95-2f22-492d-98dc-35de3b7e7b59 · outbound

This paper cites Experiment tracking with weights and biases, 2020.

Convolutional Vision Transformer for Cosmology Parameter Inference Experiment tracking with weights and biases, 2020

Reference 3

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Observation 3f50d9f4-cc88-41a9-b2bb-96d3029296c6 · outbound

This paper cites Galaxy morphology classification based on Convolutional vision Transformer (CvT).

Convolutional Vision Transformer for Cosmology Parameter Inference Galaxy morphology classification based on Convolutional vision Transformer (CvT)

Reference 4

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Observation a3c3a956-dd17-4568-ab97-db88d78d6d51 · outbound

This paper cites A new approach to observational cosmology using the scattering transform.

Convolutional Vision Transformer for Cosmology Parameter Inference A new approach to observational cosmology using the scattering transform

Reference 5

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Observation 690d2856-a6d0-40dd-b0d1-99943fb63087 · outbound

This paper cites The frontier of simulation-based inference.

Convolutional Vision Transformer for Cosmology Parameter Inference The frontier of simulation-based inference

Reference 6

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Observation 59256f3e-8ab4-4466-8f17-5968325c5b62 · outbound

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Convolutional Vision Transformer for Cosmology Parameter Inference Unresolved cited work

Reference 7

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Observation 0cea7794-25d4-43c1-b202-84bc2a126a32 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Convolutional Vision Transformer for Cosmology Parameter Inference An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 8

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Observation 559da0db-cf87-4337-a7e2-6d798c6c946f · outbound

This paper cites Strong Gravitational Lensing Parameter Estimation with Vision Transformer.

Convolutional Vision Transformer for Cosmology Parameter Inference Strong Gravitational Lensing Parameter Estimation with Vision Transformer

Reference 9

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Observation 483a9a76-5cdf-4b4c-8e6c-96371c0427bc · outbound

This paper cites Sabiu, Inkyu Park, and Sungwook E.

Convolutional Vision Transformer for Cosmology Parameter Inference Sabiu, Inkyu Park, and Sungwook E

Reference 10

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Observation 658ef94f-8d71-4f7e-90ad-99b7f38d1b6f · outbound

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Convolutional Vision Transformer for Cosmology Parameter Inference Unresolved cited work

Reference 11

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Observation 395d332f-b7aa-4d9a-81b5-77eed6f4d774 · outbound

This paper cites Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks.

Convolutional Vision Transformer for Cosmology Parameter Inference Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks

Reference 12

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Observation cb890fb2-028a-41d8-9ec8-6b7c18e006b9 · outbound

This paper cites Euclid Definition Study Report.

Convolutional Vision Transformer for Cosmology Parameter Inference Euclid Definition Study Report

Reference 13

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Observation 5e6f5d0f-d93c-4957-8e71-fc35254e4f30 · outbound

This paper cites Extracting cosmological parameters from N-body simulations using machine learning techniques.

Convolutional Vision Transformer for Cosmology Parameter Inference Extracting cosmological parameters from N-body simulations using machine learning techniques

Reference 14

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Observation ea8373f7-aef2-4bc6-9103-89e2072215e2 · outbound

This paper cites On the accuracy and precision of correlation functions and field- level inference in cosmology.

Convolutional Vision Transformer for Cosmology Parameter Inference On the accuracy and precision of correlation functions and field- level inference in cosmology

Reference 15

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Observation 929b6790-9530-450e-b7b0-5d58adaf5d88 · outbound

This paper cites SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering.

Convolutional Vision Transformer for Cosmology Parameter Inference SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering

Reference 16

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Observation c26eae88-aeb1-43a9-a65d-8dd6cb436bae · outbound

This paper cites Decoupled Weight Decay Regularization.

Convolutional Vision Transformer for Cosmology Parameter Inference Decoupled Weight Decay Regularization

Reference 17

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Observation 9b769beb-843c-470a-9e26-363b1fe165a3 · outbound

This paper cites Eisenstein, Sihan Yuan, and Lehman H.

Convolutional Vision Transformer for Cosmology Parameter Inference Eisenstein, Sihan Yuan, and Lehman H

Reference 18

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Observation 16630ce0-5339-42c7-966d-3e371702310c · outbound

This paper cites Sabiu, ZhiGang Li, HaiTao Miao, and Xiao-Dong Li.

Convolutional Vision Transformer for Cosmology Parameter Inference Sabiu, ZhiGang Li, HaiTao Miao, and Xiao-Dong Li

Reference 19

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Observation a10a51d0-f66c-45b0-93b9-27a57960a3e3 · outbound

This paper cites Estimating Cosmological Parameters from the Dark Matter Distribution.

Convolutional Vision Transformer for Cosmology Parameter Inference Estimating Cosmological Parameters from the Dark Matter Distribution

Reference 20

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Observation 4057e055-6bd8-4214-9066-d5b03be84e90 · outbound

This paper cites An improved cosmological parameter infer- ence scheme motivated by deep learning.

Convolutional Vision Transformer for Cosmology Parameter Inference An improved cosmological parameter infer- ence scheme motivated by deep learning

Reference 21

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Observation 7ddae4b5-f260-4939-8705-3a176f29709a · outbound

This paper cites Weak lensing cosmology with convolutional neural networks on noisy data.

Convolutional Vision Transformer for Cosmology Parameter Inference Weak lensing cosmology with convolutional neural networks on noisy data

Reference 22

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Observation e0deacfa-225a-45d5-8868-3254bea215be · outbound

This paper cites Kreisch, Andrina Nicola, Justin Alsing, Roman Scoccimarro, Licia Verde, Matteo Viel, Shirley Ho, Stephane Mallat, Benjamin Wandelt, and David N.

Convolutional Vision Transformer for Cosmology Parameter Inference Kreisch, Andrina Nicola, Justin Alsing, Roman Scoccimarro, Licia Verde, Matteo Viel, Shirley Ho, Stephane Mallat, Benjamin Wandelt, and David N

Reference 23

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Observation e6b66f7c-2157-4f5a-870f-aa4312bfc6f7 · outbound

This paper cites Multifield Cosmology with Artificial Intelligence.

Convolutional Vision Transformer for Cosmology Parameter Inference Multifield Cosmology with Artificial Intelligence

Reference 24

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Observation 1c5a90b4-dfc1-4c4e-a468-4c4388f2db24 · outbound

This paper cites Spergel, Rachel S.

Convolutional Vision Transformer for Cosmology Parameter Inference Spergel, Rachel S

Reference 25

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Observation ad6687e0-d433-4f45-b37f-1f302491447b · outbound

This paper cites CvT: Introducing Convolutions to Vision Transformers.

Convolutional Vision Transformer for Cosmology Parameter Inference CvT: Introducing Convolutions to Vision Transformers

Reference 26

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This paper cites Training details.

Convolutional Vision Transformer for Cosmology Parameter Inference Training details

Reference 27

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Pith citing papers

Observation ebe200c6-3789-4dd0-aeec-2fa1fea8c7b3 · inbound

ViT-based Local Volume dwarf galaxy Identificationin (VIDA) in the CSST survey cites this paper.

ViT-based Local Volume dwarf galaxy Identificationin (VIDA) in the CSST survey Convolutional Vision Transformer for Cosmology Parameter Inference

Reference 24

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Observation 77dbaddf-80ed-4485-b75c-5bd3baa8386a · inbound

Field-level weak lensing cosmology with $<100$ simulations using multifidelity simulation-based inference cites this paper.

Field-level weak lensing cosmology with $<100$ simulations using multifidelity simulation-based inference Convolutional Vision Transformer for Cosmology Parameter Inference

Reference 116

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