Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1906.04893.
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
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, observed 2026-08-11T12:42:29.075947Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T10:34:29.415228Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation f5823ddb-b50f-4a7d-b730-9943da548d0f · inbound
Robust Optimal Safe and Stability Guaranteeing Reinforcement Learning Control for Quadcopter Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 20bc2f1d-7bb7-4236-a38a-7fd3040d3fdc · inbound
Parallel Decoder Transformer: Planner-Conditioned Latent Coordination for Model-Intrinsic Parallel Generation Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9ebf826c-5c6b-4646-86e6-2598678badf9 · inbound
Does Order Matter : Connecting The Law of Robustness to Robust Generalization Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b5f5816a-c16a-449a-b53b-88e84fd7337e · inbound
A Nonlinear Separation Principle via Contraction Theory: Applications to Neural Networks, Control, and Learning Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.