Paper Citation Record · LEDGER

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys

As of 17 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2505.22574.

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

pith.paper-citation-record.v1
2505.22574 v2

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Outbound references

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This paper cites The Simons Observatory: Science goals and forecasts.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys The Simons Observatory: Science goals and forecasts

Reference 1

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This paper cites The Simons Observatory: Science Goals and Forecasts for the Enhanced Large Aperture Telescope.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys The Simons Observatory: Science Goals and Forecasts for the Enhanced Large Aperture Telescope

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This paper cites Snowmass 2021 CMB-S4 White Paper.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Snowmass 2021 CMB-S4 White Paper

Reference 3

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys CMB-HD: An Ultra-Deep, High-Resolution Millimeter-Wave Survey Over Half the Sky

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Efficient Computation of CMB anisotropies in closed FRW models

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This paper cites The Cosmic Linear Anisotropy Solving System (CLASS) I: Overview.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys The Cosmic Linear Anisotropy Solving System (CLASS) I: Overview

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys The Cosmic Linear Anisotropy Solving System (CLASS) II: Approximation schemes

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This paper cites Investigating Late-Time Dark Energy and Massive Neutrinos in Light of DESI Y1 BAO.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Investigating Late-Time Dark Energy and Massive Neutrinos in Light of DESI Y1 BAO

Reference 8

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Hajian, Phys

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This paper cites Capse.jl: efficient and auto-differentiable CMB power spectra emulation.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Capse.jl: efficient and auto-differentiable CMB power spectra emulation

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This paper cites Cosmology From CMB Lensing and Delensed EE Power Spectra Using 2019-2020 SPT-3G Polarization Data.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Cosmology From CMB Lensing and Delensed EE Power Spectra Using 2019-2020 SPT-3G Polarization Data

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys CosmoPower-JAX: high-dimensional Bayesian inference with differentiable cosmological emulators

Reference 12

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys NAUTILUS: boosting Bayesian importance nested sampling with deep learning

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This paper cites MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Cosmological perturbations without the Boltzmann hierarchy

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This paper cites COSMOPOWER: emulating cosmological power spectra for accelerated Bayesian inference from next-generation surveys.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys COSMOPOWER: emulating cosmological power spectra for accelerated Bayesian inference from next-generation surveys

Reference 16

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This paper cites A complete framework for cosmological emulation and inference with CosmoPower.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys A complete framework for cosmological emulation and inference with CosmoPower

Reference 17

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys CoLFI: Cosmological Likelihood-free Inference with Neural Density Estimators

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This paper cites High-accuracy emulators for observables in $\Lambda$CDM, $N_\mathrm{eff}$, $\Sigma m_\nu$, and $w$ cosmologies.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys High-accuracy emulators for observables in $\Lambda$CDM, $N_\mathrm{eff}$, $\Sigma m_\nu$, and $w$ cosmologies

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part I: Forecasting the Growth-Geometry split

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Attention-Based Neural Network Emulators for Multi-Probe Data Vectors Part II: Assessing Tension Metrics

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Dark Energy Survey Year 3 Results: Multi-Probe Modeling Strategy and Validation

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Bengio, P

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys On the difficulty of training Recurrent Neural Networks

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Deep Residual Learning for Image Recognition

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Attention Is All You Need

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Katharopoulos, A

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Unresolved cited work

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Linear Attention Mechanism: An Efficient Attention for Semantic Segmentation

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Planck 2018 results. VI. Cosmological parameters

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Dolga, L

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Reformer: The Efficient Transformer

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys An Attention Free Transformer

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys SPECULATOR: Emulating stellar population synthesis for fast and accurate galaxy spectra and photometry

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys CONNECT: A neural network based framework for emulating cosmological observables and cosmological parameter inference

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Radical Compression of Cosmic Microwave Background Data

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Joint Bayesian component separation and CMB power spectrum estimation

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Planck 2018 results. V. CMB power spectra and likelihoods

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys A Python compressed low-$\ell$ Planck likelihood for temperature and polarization

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Latin Hypercubes and Space-filling Designs

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys The Damping Tail of CMB Anisotropies

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Neural network based emulation of galaxy power spectrum covariances -- A reanalysis of BOSS DR12 data

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys RoFormer: Enhanced Transformer with Rotary Position Embedding

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys The Atacama Cosmology Telescope: DR6 Constraints on Extended Cosmological Models

Reference 44

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Cosmological Parameter Forecasts for a CMB-HD Survey

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys The Cosmic Linear Anisotropy Solving System (CLASS) III: Comparision with CAMB for LambdaCDM

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Planck 2018 results. I. Overview and the cosmological legacy of Planck

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Falsifying Paradigms for Cosmic Acceleration

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys 1D Convolutional Neural Networks and Applications: A Survey

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Pandya, Y

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Observation 9fc64afc-b10f-4e1b-8dc0-6b36844f711c · outbound

This paper cites Analytical emulator for the linear matter power spec- trum from physics-informed machine learning,.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Analytical emulator for the linear matter power spec- trum from physics-informed machine learning,

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This paper cites syren-halofit: A fast, interpretable, high-precision formula for the $\Lambda$CDM nonlinear matter power spectrum.

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys syren-halofit: A fast, interpretable, high-precision formula for the $\Lambda$CDM nonlinear matter power spectrum

Reference 53

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Unresolved cited work

Reference 54

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Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl

Reference 55

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Floquet Dissipative Phase Transitions cites this paper.

Floquet Dissipative Phase Transitions Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys

Reference 51

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