Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T13:30:52.371794Z
Paper Citation Record · LEDGER
As of 13 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2411.16200.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T13:30:52.371794Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
49 of 49 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 1387cca6-ab23-4133-824a-e7372b6f9727 · outbound
Reference 1
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape B onfanti and W
Reference 2
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape C ybenko, Approximation by superpositions of a sigmoidal function, Mathematics of Control, Signals and Systems, 2 (1989), pp
Reference 5
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape D aneshmand, J
Reference 6
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Reference 10
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape Semi-flat minima and saddle points by embedding neural networks to overparameterization
Reference 11
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Reference 12
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Reference 13
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape Unresolved cited work
Reference 16
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape H eidrich and W
Reference 17
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape H enkelman and H
Reference 18
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape H ornik, Approximation capabilities of multilayer feedforward networks , Neural Networks, 4 (1991), pp
Reference 19
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Reference 21
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape K ingma and J
Reference 22
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Reference 23
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape L ongsine and S
Reference 25
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape Unresolved cited work
Reference 26
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape Accelerated high-index saddle dynamics method for searching high-index saddle points
Reference 27
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape M ehta, Finding all the stationary points of a potential-energy landscape via numerical polynomial- homotopy-continuation method, Physical Review E, 84 (2011), p
Reference 28
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape M ilnor, Morse Theory
Reference 29
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Reference 30
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape Nesterov, A method for solving the convex programming problem with convergence rate o(1/k2), Proceed- ings of the USSR Academy of Sciences, 269 (1983), pp
Reference 31
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape O’D onoghue and E
Reference 32
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Reference 33
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape P oly ak, Some methods of speeding up the convergence of iteration methods , Ussr Computational Mathe- matics and Mathematical Physics, 4 (1964), pp
Reference 34
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape https: //pytorch.org/docs/stable/generated/torch.optim.lr scheduler.StepLR.html, 2023
Reference 35
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Reference 36
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape S amanta, M
Reference 37
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Reference 41
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Reference 42
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Reference 45
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Reference 46
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Reference 47
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Reference 48
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Reference 49
Source-reported events for the cited work
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No inbound Pith citation observations are available.