Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals | Paper Citation Record

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This paper cites Evolution-informed forecasting of seasonal influenza a (h3n2).

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Evolution-informed forecasting of seasonal influenza a (h3n2)

Reference 1

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This paper cites Vaccination of dogs in an african city interrupts rabies transmission and reduces human exposure.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Vaccination of dogs in an african city interrupts rabies transmission and reduces human exposure

Reference 2

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Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Measuring competitive exclusion in non–small cell lung cancer

Reference 3

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Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals A simpler model of the human circadian pacemaker

Reference 4

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Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Enhanced circadian phase tracking: A 5-h dlmo sampling protocol using wearable data

Reference 5

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This paper cites A predictive model of gene expression reveals the role of network motifs in the mating response of yeast.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals A predictive model of gene expression reveals the role of network motifs in the mating response of yeast

Reference 6

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This paper cites Parameter estimation of power elec- tronic converters with physics-informed machine learning.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Parameter estimation of power elec- tronic converters with physics-informed machine learning

Reference 7

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Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Differentially private sgd with non- smooth losses

Reference 8

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Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals A software package for sequential quadratic programming

Reference 9

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This paper cites Algorithm 778: L-bfgs-b: Fortran subroutines for large-scale bound-constrained optimization.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Algorithm 778: L-bfgs-b: Fortran subroutines for large-scale bound-constrained optimization

Reference 10

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Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals The levenberg-marquardt algorithm: implementation and theory

Reference 11

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This paper cites Neural ordinary differential equations.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Neural ordinary differential equations

Reference 12

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This paper cites Implementing the nelder-mead simplex algorithm with adaptive parameters.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Implementing the nelder-mead simplex algorithm with adaptive parameters

Reference 13

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This paper cites Differential evolution: a practical approach to global optimization.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Differential evolution: a practical approach to global optimization

Reference 14

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This paper cites Smoothing and worst-case complexity for direct-search methods in nonsmooth optimization.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Smoothing and worst-case complexity for direct-search methods in nonsmooth optimization

Reference 15

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This paper cites Linearly constrained nonsmooth and nonconvex minimization.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Linearly constrained nonsmooth and nonconvex minimization

Reference 16

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This paper cites The admm-pinns algorithmic framework for nonsmooth pde-constrained optimization: a deep learning approach.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals The admm-pinns algorithmic framework for nonsmooth pde-constrained optimization: a deep learning approach

Reference 17

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This paper cites Deep neural networks learn non-smooth functions effectively.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Deep neural networks learn non-smooth functions effectively

Reference 18

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This paper cites The gap between theory and practice in function approximation with deep neural networks.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals The gap between theory and practice in function approximation with deep neural networks

Reference 19

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This paper cites Numerical methods for optimal control with binary control functions applied to a lotka- volterra type fishing problem.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Numerical methods for optimal control with binary control functions applied to a lotka- volterra type fishing problem

Reference 20

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This paper cites Bolt-on differential privacy for scalable stochastic gradient descent-based analytics.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Bolt-on differential privacy for scalable stochastic gradient descent-based analytics

Reference 21

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Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Unresolved cited work

Reference 22

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This paper cites Private stochastic convex optimization: optimal rates in linear time.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Private stochastic convex optimization: optimal rates in linear time

Reference 23

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This paper cites Stability of stochastic gradient descent on nonsmooth convex losses.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Stability of stochastic gradient descent on nonsmooth convex losses

Reference 24

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This paper cites The effects of self-selected light-dark cycles and social constraints on human sleep and circadian timing: a modeling approach.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals The effects of self-selected light-dark cycles and social constraints on human sleep and circadian timing: a modeling approach

Reference 25

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This paper cites Optimal adjust- ment of the human circadian clock in the real world.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Optimal adjust- ment of the human circadian clock in the real world

Reference 26

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This paper cites Predicting circadian misalignment with wearable technology: validation of wrist- worn actigraphy and photometry in night shift workers.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Predicting circadian misalignment with wearable technology: validation of wrist- worn actigraphy and photometry in night shift workers

Reference 27

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This paper cites Predicting circadian phase across populations: a comparison of mathematical models and wearable devices.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Predicting circadian phase across populations: a comparison of mathematical models and wearable devices

Reference 28

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This paper cites Personalized sleep-wake patterns aligned with circadian rhythm relieve daytime sleepiness.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Personalized sleep-wake patterns aligned with circadian rhythm relieve daytime sleepiness

Reference 29

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Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals A real-time, personalized sleep intervention using mathematical modeling and wearable devices

Reference 30

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This paper cites A digital, real-time, history-based sleep- management tool to enhance alertness.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals A digital, real-time, history-based sleep- management tool to enhance alertness

Reference 31

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This paper cites Model-based hu- man circadian phase estimation using a particle filter.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Model-based hu- man circadian phase estimation using a particle filter

Reference 32

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This paper cites Parameter estimation in a model of the human circadian pacemaker using a particle filter.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Parameter estimation in a model of the human circadian pacemaker using a particle filter

Reference 33

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This paper cites The role of light sensitivity and intrinsic circadian period in predicting individual circadian timing.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals The role of light sensitivity and intrinsic circadian period in predicting individual circadian timing

Reference 34

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This paper cites Extracting circadian and sleep parameters from longitudinal data in schizophrenia for the design of pragmatic light interventions.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Extracting circadian and sleep parameters from longitudinal data in schizophrenia for the design of pragmatic light interventions

Reference 35

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Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Unresolved cited work

Reference 36

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This paper cites Implicit neural representations with periodic activation functions.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Implicit neural representations with periodic activation functions

Reference 37

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This paper cites Fourier features let networks learn high frequency functions in low dimensional domains.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Fourier features let networks learn high frequency functions in low dimensional domains

Reference 38

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This paper cites Shallow univariate relu networks as splines: initialization, loss surface, hessian, and gradient flow dynamics.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Shallow univariate relu networks as splines: initialization, loss surface, hessian, and gradient flow dynamics

Reference 39

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Observation 553fc0f7-1416-4b5e-b5bf-27136d24f307 · outbound

This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:30:40.748795Z

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Observation bdd33104-b836-4b3a-ab75-6b9dbefc4073 · outbound

This paper cites Characterizing possible failure modes in physics-informed neural networks.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Characterizing possible failure modes in physics-informed neural networks

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:30:40.701829Z

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Observation a24170a6-96ea-41ec-b6ab-09ccc1c66a42 · outbound

This paper cites Physics-informed machine learning.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Physics-informed machine learning

Reference 42

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This paper cites Deep Neural Network Approach to Forward-Inverse Problems.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Deep Neural Network Approach to Forward-Inverse Problems

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:30:39.910737Z

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This paper cites Trend to equilibrium for the kinetic fokker-planck equation via the neural network approach.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Trend to equilibrium for the kinetic fokker-planck equation via the neural network approach

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:30:40.637841Z

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Observation 1d6c3621-022a-40c6-bae4-ebb115a37cbd · outbound

This paper cites Real-world implications of a rapidly responsive covid-19 spread model with time-dependent parameters via deep learn- ing: Model development and validation.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Real-world implications of a rapidly responsive covid-19 spread model with time-dependent parameters via deep learn- ing: Model development and validation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:30:40.605465Z

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Observation d78ecb0d-e22f-4236-adff-10697e73ee00 · outbound

This paper cites Density physics-informed neural networks reveal sources of cell heterogeneity in signal transduction.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Density physics-informed neural networks reveal sources of cell heterogeneity in signal transduction

Reference 46

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Observation 985cc029-e0a2-47bb-acbb-a8082eadd0a1 · outbound

This paper cites Sensitivity analysis of ordinary differential equation systems—a direct method.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Sensitivity analysis of ordinary differential equation systems—a direct method

Reference 47

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Observation b0ea98d5-c92b-4cf7-87c1-6f2819e1bbed · outbound

This paper cites Principles of discontinuous dynamical systems.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Principles of discontinuous dynamical systems

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:30:40.526771Z

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Observation e80a220c-31d3-4ccb-b1f4-d3cfed67727a · outbound

This paper cites Convergence and complexity analysis of a levenberg–marquardt algorithm for inverse problems.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Convergence and complexity analysis of a levenberg–marquardt algorithm for inverse problems

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:30:40.455816Z

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Observation ad5cf2a2-8ac8-4040-a939-92999c6e054a · outbound

This paper cites A generalized gronwall inequality and its application to a fractional differential equation.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals A generalized gronwall inequality and its application to a fractional differential equation

Reference 50

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This paper cites Minimum Width for Universal Approximation.

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals Minimum Width for Universal Approximation

Reference 51

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