Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification | Paper Citation Record

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This paper cites The range and probability distribution for this must be carefully chosen to minimize introduced bias.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification The range and probability distribution for this must be carefully chosen to minimize introduced bias

Reference 1

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This paper cites In other words, the independent variable and the uncertainty are the same for the pseudodata as for the actual data.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification In other words, the independent variable and the uncertainty are the same for the pseudodata as for the actual data

Reference 2

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This paper cites For instance, in our example ofρ(770)-resonance, we only retain data points with physical poles in a realistic range.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification For instance, in our example ofρ(770)-resonance, we only retain data points with physical poles in a realistic range

Reference 3

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This paper cites The valuesyp i are used as the inputs of the neural network and the randomly generated⃗ aused as outputs.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification The valuesyp i are used as the inputs of the neural network and the randomly generated⃗ aused as outputs

Reference 4

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Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Unresolved cited work

Reference 5

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Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Unresolved cited work

Reference 6

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Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Unresolved cited work

Reference 7

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Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Unresolved cited work

Reference 8

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This paper cites Training deep neural density estimators to identify mechanistic models of neural dynamics,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Training deep neural density estimators to identify mechanistic models of neural dynamics,

Reference 9

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This paper cites Specifically, random noise is added to the phase-shift generated from an exponential distribution given bye−(x−1)λλforx>0, withλ= 0.05.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Specifically, random noise is added to the phase-shift generated from an exponential distribution given bye−(x−1)λλforx>0, withλ= 0.05

Reference 10

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Observation 9df90db5-c028-47fa-9f9d-637f8215c568 · outbound

This paper cites Inferring coalescence times from DNA sequence data,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Inferring coalescence times from DNA sequence data,

Reference 11

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Observation 86f9364d-6b4f-40c2-9681-d6c1ac339ac1 · outbound

This paper cites Bayesianly justifiable and relevant frequency calculations for the applied statistician,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Bayesianly justifiable and relevant frequency calculations for the applied statistician,

Reference 12

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Observation f1ddde9e-d2dd-4b7b-be7c-e72bc3611dbb · outbound

This paper cites Monte Carlo methods of inference for implicit statistical models,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Monte Carlo methods of inference for implicit statistical models,

Reference 13

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This paper cites Approximate Bayesian computation in population genetics,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Approximate Bayesian computation in population genetics,

Reference 14

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Observation b2f97f4b-63bd-46f1-80de-44e4a2b88a3a · outbound

This paper cites Simulation-based inference methods for particle physics.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Simulation-based inference methods for particle physics

Reference 15

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Observation 814c992b-d9f2-4afe-b52b-2a503dc4b4bf · outbound

This paper cites Inferring dark matter substructure with astrometric lensing beyond the power spectrum.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Inferring dark matter substructure with astrometric lensing beyond the power spectrum

Reference 16

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This paper cites Simulation-Based Inference of Strong Gravitational Lensing Parameters.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Simulation-Based Inference of Strong Gravitational Lensing Parameters

Reference 17

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This paper cites Predicting the mpemba effect using machine learning,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Predicting the mpemba effect using machine learning,

Reference 18

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This paper cites Roy equation analysis of pi pi scattering.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Roy equation analysis of pi pi scattering

Reference 19

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This paper cites Simulation- based inference of evolutionary parameters from adaptation dynamics using neural networks,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Simulation- based inference of evolutionary parameters from adaptation dynamics using neural networks,

Reference 20

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This paper cites A tutorial on simulation-based inference,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification A tutorial on simulation-based inference,

Reference 21

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Observation 78ce3d2e-1233-4364-b251-adb326bba5fd · outbound

This paper cites Investigating the Impact of Model Misspecification in Neural Simulation-based Inference.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Investigating the Impact of Model Misspecification in Neural Simulation-based Inference

Reference 22

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This paper cites Tests for model misspecification in simulation-based inference: from local distortions to global model checks.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Tests for model misspecification in simulation-based inference: from local distortions to global model checks

Reference 23

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This paper cites Learning Robust Statistics for Simulation-based Inference under Model Misspecification.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Learning Robust Statistics for Simulation-based Inference under Model Misspecification

Reference 24

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This paper cites Addressing Misspecification in Simulation-based Inference through Data-driven Calibration.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Addressing Misspecification in Simulation-based Inference through Data-driven Calibration

Reference 25

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This paper cites Theory of resonances.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Theory of resonances

Reference 26

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This paper cites ππPartial Wave Analysis from Reactionsπ +p→ π+π−∆++ andπ +p→K +K−∆++ at 7.1-GeV/c,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification ππPartial Wave Analysis from Reactionsπ +p→ π+π−∆++ andπ +p→K +K−∆++ at 7.1-GeV/c,

Reference 27

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This paper cites ππPhase Shift Analysis Below theK ¯KThreshold,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification ππPhase Shift Analysis Below theK ¯KThreshold,

Reference 28

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This paper cites $P$-wave $\pi\pi$ scattering and the $\rho$ resonance from lattice QCD.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification $P$-wave $\pi\pi$ scattering and the $\rho$ resonance from lattice QCD

Reference 29

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This paper cites \pi\pi scattering.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification \pi\pi scattering

Reference 30

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This paper cites The pion-pion scattering amplitude. IV: Improved analysis with once subtracted Roy-like equations up to 1100 MeV.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification The pion-pion scattering amplitude. IV: Improved analysis with once subtracted Roy-like equations up to 1100 MeV

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Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Two-pion contribution to hadronic vacuum polarization

Reference 32

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This paper cites Global parameterization of $\pi \pi$ scattering up to 2 GeV.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Global parameterization of $\pi \pi$ scattering up to 2 GeV

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This paper cites $\rho$ Meson Decay in 2+1 Flavor Lattice QCD.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification $\rho$ Meson Decay in 2+1 Flavor Lattice QCD

Reference 34

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Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Energy dependence of the {\rho} resonance in {\pi}{\pi} elastic scattering from lattice QCD

Reference 35

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This paper cites $\rho$ and $K^*$ resonances on the lattice at nearly physical quark masses and $N_f=2$.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification $\rho$ and $K^*$ resonances on the lattice at nearly physical quark masses and $N_f=2$

Reference 36

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This paper cites Coupled $\pi\pi, K\overline{K}$ scattering in $P$-wave and the $\rho$ resonance from lattice QCD.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Coupled $\pi\pi, K\overline{K}$ scattering in $P$-wave and the $\rho$ resonance from lattice QCD

Reference 37

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This paper cites Studying the $\rho$ resonance parameters with staggered fermions.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Studying the $\rho$ resonance parameters with staggered fermions

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This paper cites Universal parameters of the $\Lambda(1380)$, the $\Lambda(1405)$ and their isospin partners from a combined analysis of Lattice QCD and experimental results.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Universal parameters of the $\Lambda(1380)$, the $\Lambda(1405)$ and their isospin partners from a combined analysis of Lattice QCD and experimental results

Reference 39

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This paper cites The $I=1$ pion-pion scattering amplitude and timelike pion form factor from $N_{\rm f} = 2+1$ lattice QCD.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification The $I=1$ pion-pion scattering amplitude and timelike pion form factor from $N_{\rm f} = 2+1$ lattice QCD

Reference 40

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This paper cites Hadron-Hadron Interactions from $N_f=2+1+1$ Lattice QCD: The $\rho$-resonance.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Hadron-Hadron Interactions from $N_f=2+1+1$ Lattice QCD: The $\rho$-resonance

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This paper cites Extraction of isoscalar $\pi\pi$ phase-shifts from lattice QCD.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Extraction of isoscalar $\pi\pi$ phase-shifts from lattice QCD

Reference 42

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Observation f05a6e1e-52a1-42f7-9f1f-f6366f681d75 · outbound

This paper cites Chiral Extrapolations of the $\boldsymbol{\rho(770)}$ Meson in $\mathbf{N_f=2+1}$ Lattice QCD Simulations.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Chiral Extrapolations of the $\boldsymbol{\rho(770)}$ Meson in $\mathbf{N_f=2+1}$ Lattice QCD Simulations

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Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.617122Z

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This paper cites Two-flavor simulations of theρ(770) and the role of theK Kchannel,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Two-flavor simulations of theρ(770) and the role of theK Kchannel,

Reference 44

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This paper cites Rho resonance parameters from lattice QCD.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Rho resonance parameters from lattice QCD

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Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.628049Z

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This paper cites The $\rho$-resonance with physical pion mass from $N_f=2$ lattice QCD.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification The $\rho$-resonance with physical pion mass from $N_f=2$ lattice QCD

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Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.632379Z

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This paper cites Bayesian Analysis and Analytic Continuation of Scattering Amplitudes from Lattice QCD,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Bayesian Analysis and Analytic Continuation of Scattering Amplitudes from Lattice QCD,

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Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.636875Z

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This paper cites S- and p-wave structure of $S=-1$ meson-baryon scattering in the resonance region.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification S- and p-wave structure of $S=-1$ meson-baryon scattering in the resonance region

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This paper cites Three-body resonances in the $\varphi^4$ theory.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Three-body resonances in the $\varphi^4$ theory

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This paper cites Review of the ${\mathbf \Lambda}$(1405): A curious case of a strange-ness resonance.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Review of the ${\mathbf \Lambda}$(1405): A curious case of a strange-ness resonance

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This paper cites J\"ulich-Bonn-Washington Model for Pion Electroproduction Multipoles.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification J\"ulich-Bonn-Washington Model for Pion Electroproduction Multipoles

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Observation 49c76598-8e8b-4c3b-8a79-f019a52c5ad1 · outbound

This paper cites Three-body Unitarity with Isobars Revisited.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Three-body Unitarity with Isobars Revisited

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This paper cites Dalitz plots and lineshape of $a_1(1260)$ from a relativistic three-body unitary approach.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Dalitz plots and lineshape of $a_1(1260)$ from a relativistic three-body unitary approach

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Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.661058Z

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This paper cites Pole position of the $a_1(1260)$ resonance in a three-body unitary framework.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Pole position of the $a_1(1260)$ resonance in a three-body unitary framework

Reference 54

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Observation e8781552-a7a0-4efc-aeed-0287f4781ca3 · outbound

This paper cites Three-body dynamics of the $a_1(1260)$ resonance from lattice QCD.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Three-body dynamics of the $a_1(1260)$ resonance from lattice QCD

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.669558Z

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Observation 76608f14-9295-469c-bd4f-580e2b76a1da · outbound

This paper cites A unitary coupled-channel three-body amplitude with pions and kaons.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification A unitary coupled-channel three-body amplitude with pions and kaons

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.673561Z

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Observation 980ac113-9426-462f-80f4-6a5dd37e635c · outbound

This paper cites $\omega$ meson from lattice QCD.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification $\omega$ meson from lattice QCD

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.677774Z

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Observation 7163a559-428a-4055-92e0-a0cc5b961a76 · outbound

This paper cites Dynamical coupled-channel models for hadron dynamics,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Dynamical coupled-channel models for hadron dynamics,

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.681799Z

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Observation 72613bc8-7721-40a0-88af-d6a9937afd7c · outbound

This paper cites Three-body scattering in isobar ansatz,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Three-body scattering in isobar ansatz,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.728715Z

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Observation ad71daca-5b8d-4864-8fc2-8b3856f4cc8d · outbound

This paper cites Multi-particle systems on the lattice and chiral extrapolations: a brief review.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Multi-particle systems on the lattice and chiral extrapolations: a brief review

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.690461Z

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Observation 29a4dcae-a369-47f0-a88b-40f678f53d8b · outbound

This paper cites Finite-volume energy spectrum of the $K^-K^-K^-$ system.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Finite-volume energy spectrum of the $K^-K^-K^-$ system

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.694765Z

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Observation 5f65dbdc-3a34-4842-93a9-b28822341425 · outbound

This paper cites Three pion spectrum in the $I=3$ channel from lattice QCD.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Three pion spectrum in the $I=3$ channel from lattice QCD

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.698772Z

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Observation d948acbd-15af-453d-9943-60418d2106c7 · outbound

This paper cites Three-body unitarity versus finite-volume $\pi^+\pi^+\pi^+$ spectrum from lattice QCD.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Three-body unitarity versus finite-volume $\pi^+\pi^+\pi^+$ spectrum from lattice QCD

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.702998Z

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Observation e9000177-9f5e-48c1-8f4f-31fd94a5f817 · outbound

This paper cites A cross-channel study of pion scattering from lattice QCD.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification A cross-channel study of pion scattering from lattice QCD

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.707717Z

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Observation e87fa0e7-aecc-47d9-92a4-d752a024508b · outbound

This paper cites Pion scattering in the isospin I=2 channel from elongated lattices.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Pion scattering in the isospin I=2 channel from elongated lattices

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.712043Z

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Observation dcb472d8-f605-4cf4-a398-4f37374c2da0 · outbound

This paper cites 3-body quantization condition in a unitary formalism.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification 3-body quantization condition in a unitary formalism

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.716454Z

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Observation 49399430-e792-4979-8464-4c1281e4b2a0 · outbound

This paper cites Finite-volume spectrum of $\pi^+\pi^+$ and $\pi^+\pi^+\pi^+$ systems.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Finite-volume spectrum of $\pi^+\pi^+$ and $\pi^+\pi^+\pi^+$ systems

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.720450Z

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Observation 9428ede9-ba22-4218-8965-69e01899b1c8 · outbound

This paper cites Three-body spectrum in a finite volume: the role of cubic symmetry.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Three-body spectrum in a finite volume: the role of cubic symmetry

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.724647Z

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Observation b3f073a3-2bfb-4a20-9157-32b20571781d · outbound

This paper cites Line shape analysis of $\Lambda(1405)$ in $\gamma p \rightarrow K^+\Sigma^-\pi^+$ reaction using convolutional neural network.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Line shape analysis of $\Lambda(1405)$ in $\gamma p \rightarrow K^+\Sigma^-\pi^+$ reaction using convolutional neural network

Reference 69

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:13:14.362401Z

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Observation 448355c9-fae5-49e3-a687-fd705b8ce7f3 · outbound

This paper cites Three-body Unitarity in the Finite Volume.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Three-body Unitarity in the Finite Volume

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.732499Z

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Observation 07e658df-d77f-4a80-8d10-a7733d83c1a6 · outbound

This paper cites A lattice model of heavy-light three-body system.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification A lattice model of heavy-light three-body system

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.737189Z

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Observation 403857cf-a484-439c-8c96-26eb527484e9 · outbound

This paper cites Variational approach to $N$-body interactions in finite volume.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Variational approach to $N$-body interactions in finite volume

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.741936Z

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Observation 65f1bc50-59cf-4b70-8393-1735cb8c1122 · outbound

This paper cites Dalitz-plot decomposition for three-body decays.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Dalitz-plot decomposition for three-body decays

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.746132Z

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Observation 108703fc-bac7-44fd-9a7f-298dfd21f335 · outbound

This paper cites Khuri-Treiman equations for $3\pi$ decays of particles with spin.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Khuri-Treiman equations for $3\pi$ decays of particles with spin

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.750211Z

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Observation c89dd47a-2a74-4a08-9bb8-dacd6a55f171 · outbound

This paper cites Three-body scattering: Ladders and Resonances.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Three-body scattering: Ladders and Resonances

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.754260Z

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Observation 1b0e9e76-028b-4a92-8a61-1eaa1e30dd74 · outbound

This paper cites Deep Learning Exotic Hadrons.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Deep Learning Exotic Hadrons

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.758595Z

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Observation 3c979f4e-ec74-4eee-9513-61151cdcc03d · outbound

This paper cites Machine learning exotic hadrons,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Machine learning exotic hadrons,

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.762495Z

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Observation 56bc04e8-d4ff-4d73-ac5c-4d7481079a67 · outbound

This paper cites Pole structure of $P_\psi^N(4312)^+$ via machine learning and uniformized S-matrix.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Pole structure of $P_\psi^N(4312)^+$ via machine learning and uniformized S-matrix

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.766013Z

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Observation 9ba803b9-779b-4fe9-96fa-1c8165ff0e06 · outbound

This paper cites Classifying Pole of Amplitude Using Deep Neural Network.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Classifying Pole of Amplitude Using Deep Neural Network

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.812905Z

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Observation 9f258b93-5bb7-43f5-a25a-dbce17718473 · outbound

This paper cites Meson mass and width: Deep learning approach.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Meson mass and width: Deep learning approach

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.773838Z

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Observation a0e55b83-52ef-4555-be34-3c61b14a07f0 · outbound

This paper cites Analysis of hidden-charm pentaquarks as triangle singularities via deep learning.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Analysis of hidden-charm pentaquarks as triangle singularities via deep learning

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.778018Z

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Observation e144ce6d-224a-4af9-bf43-815095018f29 · outbound

This paper cites Reconstructing $S$-matrix Phases with Machine Learning.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Reconstructing $S$-matrix Phases with Machine Learning

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.781916Z

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Observation b6696ca5-98ef-4c9d-a756-579a02d181eb · outbound

This paper cites Feature extraction in partial wave analysis using $K$-matrix approach.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Feature extraction in partial wave analysis using $K$-matrix approach

Reference 83

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:13:14.304033Z

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Observation 24b3da50-e9f2-415f-beec-a2f1a24158cf · outbound

This paper cites A Deep Learning Framework for Disentangling Triangle Singularity and Pole-Based Enhancements.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification A Deep Learning Framework for Disentangling Triangle Singularity and Pole-Based Enhancements

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.790199Z

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Observation 1a1b918a-36fe-4b9c-a215-c81d4f6abcff · outbound

This paper cites Extraction of S-matrix pole structure using deep learning,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Extraction of S-matrix pole structure using deep learning,

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.794658Z

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Observation a7bcd9df-b778-49a5-8bd7-b908be1be37e · outbound

This paper cites Classifying near-threshold enhancement using deep neural network.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Classifying near-threshold enhancement using deep neural network

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.798422Z

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Observation 2834bcf6-6151-4df8-af2e-7974503254f8 · outbound

This paper cites Model independent analysis of coupled-channel scattering: a deep learning approach.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Model independent analysis of coupled-channel scattering: a deep learning approach

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.803063Z

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Observation 82efecb8-ce42-414f-b2b1-1f4afeed9ee4 · outbound

This paper cites Unveiling the pole structure of S-matrix using deep learning.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Unveiling the pole structure of S-matrix using deep learning

Reference 88

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:13:14.226592Z

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Observation 7382ef47-7cfa-4b80-80fa-26ad7ea32061 · outbound

This paper cites Status of the Λ(1405),.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Status of the Λ(1405),

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.860551Z

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Observation 7ec3f4ed-c490-4268-827c-cc111801ad43 · outbound

This paper cites Towards the Minimal Spectrum of Excited Baryons.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Towards the Minimal Spectrum of Excited Baryons

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.817141Z

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Observation d46058f0-5385-4a80-9ba1-7714a4f42be4 · outbound

This paper cites Model selection for pion photoproduction,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Model selection for pion photoproduction,

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.821332Z

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Observation 105aa113-969f-4409-8dfe-cca3cdfe0b74 · outbound

This paper cites Ridge regression for minimizing the couplings of hyperon resonances in the $K^+ \Lambda$ photoproduction.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Ridge regression for minimizing the couplings of hyperon resonances in the $K^+ \Lambda$ photoproduction

Reference 92

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:13:14.180312Z

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Observation 1650a8f9-d84f-4613-be9c-6053bdfad151 · outbound

This paper cites Model selection for $K^+\Sigma^-$ photoproduction within isobar model.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Model selection for $K^+\Sigma^-$ photoproduction within isobar model

Reference 93

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:13:14.160809Z

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Observation abb13ea4-5d35-46e2-b169-a52a8d4d231c · outbound

This paper cites Toward a generative modeling analysis of CLAS exclusive $2\pi$ photoproduction.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Toward a generative modeling analysis of CLAS exclusive $2\pi$ photoproduction

Reference 94

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:13:14.141716Z

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Observation 4e808295-9467-4e03-b4c2-ed2379fed095 · outbound

This paper cites Study for a model-independent pole determination of overlapping resonances.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Study for a model-independent pole determination of overlapping resonances

Reference 95

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:13:14.123305Z

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Observation b13fff77-15a0-402b-8b48-d96bec080915 · outbound

This paper cites New insights into the pole parameters of the $\Lambda(1380)$, the $\Lambda(1405)$ and the $\Sigma(1385)$.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification New insights into the pole parameters of the $\Lambda(1380)$, the $\Lambda(1405)$ and the $\Sigma(1385)$

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.845193Z

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Observation ceed590f-63a8-44c6-84dc-4562dd8a6c59 · outbound

This paper cites New insights into the nature of the $\Lambda(1380)$ and $\Lambda(1405)$ resonances away from the SU(3) limit.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification New insights into the nature of the $\Lambda(1380)$ and $\Lambda(1405)$ resonances away from the SU(3) limit

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.849340Z

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Observation 6128d493-dfac-438a-8c93-15a63f2c9dac · outbound

This paper cites Testing chiral unitary models for the Λ(1405) in K+πΣ photoproduction,.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Testing chiral unitary models for the Λ(1405) in K+πΣ photoproduction,

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.856054Z

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Observation bc923238-c207-4652-88b8-d7eef54126b7 · outbound

This paper cites Nucleon resonance parameters from Roy-Steiner equations.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Nucleon resonance parameters from Roy-Steiner equations

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-15T18:13:13.905457Z

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Observation 2a3fc273-1c25-4515-9c88-b92950a723be · outbound

This paper cites Theoretical approaches to low energy $\bar{K}N$ interactions.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification Theoretical approaches to low energy $\bar{K}N$ interactions

Reference 100

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:13:14.083652Z

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