First detection of SO and SO2 in a B[e] supergiant ejecta, with chemical models reproducing high SO2 abundance in ~10^4 yr and low 32SO/33SO ratio attributed to photochemistry-driven fractionation.
1963 An Algorithm for Least-Squares Estimation of Nonlinear Parameters
9 Pith papers cite this work, alongside 30,435 external citations. Polarity classification is still indexing.
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Pith papers citing it
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representative citing papers
RNC-LM extends geodesic-accelerated Levenberg-Marquardt to arbitrary-order Riemann normal coordinate corrections, reusing the LM matrix factorization for all orders and achieving large speedups on PINN and potential-fitting benchmarks.
Adaptive Newton-CG methods achieve the best-known iteration complexity for epsilon-stationary points in nonconvex optimization with Holder continuous Hessians while ensuring local superlinear convergence.
A general framework for parameter-free smooth nonconvex optimization via higher-order regularization yields algorithms with optimal complexity bounds without prior parameter knowledge.
Fully implicit resolvent discretization of noisy accelerated gradient dynamics produces a Lyapunov mean-square recursion whose contraction factor improves and stationary error scales as O(1/α), vanishing for large α under accurate inner solves.
A CKM-based framework learns scatterer priors offline from path signatures and uses online matching plus NLS to localize users in NLoS ISAC scenarios, outperforming fingerprinting in simulations.
This paper isolates admissibility conditions for trust-region radius updates that guarantee first-order stationarity and O(ε^{-2}) complexity, verifies them across five mechanism classes, and extends prior frameworks with new convergence results under linear Hessian growth.
Symbolic emulators approximate key Lambda CDM functions to 0.001-0.05% accuracy across relevant redshifts and Omega_m values, enabling faster 3x2pt inference with consistent results.
Data-driven equation discovery applied to liquid film flows identifies identifiability issues from multi-collinearity in monomial bases and early-time transients with large residuals.
citing papers explorer
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Discovery of sulfur oxides in the ejecta of a B[e] supergiant
First detection of SO and SO2 in a B[e] supergiant ejecta, with chemical models reproducing high SO2 abundance in ~10^4 yr and low 32SO/33SO ratio attributed to photochemistry-driven fractionation.
-
Higher-Order Geometric Updates for Levenberg-Marquardt Method via Riemann Normal Coordinates
RNC-LM extends geodesic-accelerated Levenberg-Marquardt to arbitrary-order Riemann normal coordinate corrections, reusing the LM matrix factorization for all orders and achieving large speedups on PINN and potential-fitting benchmarks.
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Adaptive Newton-CG methods with global and local analysis for unconstrained optimization with H\"older continuous Hessian
Adaptive Newton-CG methods achieve the best-known iteration complexity for epsilon-stationary points in nonconvex optimization with Holder continuous Hessians while ensuring local superlinear convergence.
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A General Recipe for Parameter-Free Nonconvex Optimization via Higher-Order Regularization
A general framework for parameter-free smooth nonconvex optimization via higher-order regularization yields algorithms with optimal complexity bounds without prior parameter knowledge.
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IRON: Implicit Resolvent Optimization under Noise
Fully implicit resolvent discretization of noisy accelerated gradient dynamics produces a Lyapunov mean-square recursion whose contraction factor improves and stationary error scales as O(1/α), vanishing for large α under accurate inner solves.
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Channel Knowledge Map-Enabled NLoS ISAC Localization
A CKM-based framework learns scatterer priors offline from path signatures and uses online matching plus NLS to localize users in NLoS ISAC scenarios, outperforming fingerprinting in simulations.
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A survey of trust-region radius update mechanisms. Part I: First-order analysis
This paper isolates admissibility conditions for trust-region radius updates that guarantee first-order stationarity and O(ε^{-2}) complexity, verifies them across five mechanism classes, and extends prior frameworks with new convergence results under linear Hessian growth.
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Symbolic Emulators for Cosmology: Accelerating Cosmological Analyses Without Sacrificing Precision
Symbolic emulators approximate key Lambda CDM functions to 0.001-0.05% accuracy across relevant redshifts and Omega_m values, enabling faster 3x2pt inference with consistent results.
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Data-Driven Equation Discovery for Nonlinear Liquid Film Flows
Data-driven equation discovery applied to liquid film flows identifies identifiability issues from multi-collinearity in monomial bases and early-time transients with large residuals.