Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T21:07:45.482792Z
Paper Citation Record · LEDGER
As of 16 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2505.10856.
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 2026-08-15T21:07:45.482792Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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
43 of 43 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation cea80599-6367-4539-b2b3-422a4a66d5d0 · outbound
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Missing data imputation of high-resolution temporal climate time series data
Reference 1
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ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Based on this synthetic dataset, we test the representation Table 4: Details of benchmark datasets
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ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Saits: Self-attention-based imputation for time series
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Observation fc33df5b-99ab-4bff-afc8-7e5a09415ad6 · outbound
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ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Implicit neural rep- resentation in medical imaging: A comparative survey
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Reference 21
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Reference 22
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Observation 12b4c507-1577-429e-97d4-51f332a37a0c · outbound
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data https://www.nrel.gov/grid/solar- power-data.html
Reference 23
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ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Early prediction of sepsis from clinical data: the physionetcomputing in cardiology challenge
Reference 24
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ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Miner: Multiscale implicit neural repre- sentation
Reference 25
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Observation 89b9ae95-bc18-40c7-8d2d-ac1682cb4275 · outbound
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Interrupted time series analysis using autoregressive integrated moving average (arima) models: a guide for evaluating large-scale health interventions
Reference 26
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Observation 4dd38b1a-fd5b-49bd-a084-27ee6d2eb542 · outbound
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Reference 28
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Reference 30
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Reference 33
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Reference 34
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Reference 35
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Reference 36
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ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Estimating missing data in temporal data streams using multi-directional recurrent neural net- works
Reference 37
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Observation f970ab19-071c-4269-a3f9-7cd839faddc2 · outbound
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Are transformers effective for time series fore- casting? In Proceedings of the AAAI conference on artifi- cial intelligence, volume 37, pages 11121–11128,
Reference 38
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Observation 65c9763a-4279-4933-ac86-3c3657c39fa0 · outbound
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Cautionary tales on air-quality improvement in beijing
Reference 39
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Reference 41
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ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data One fits all: Power general time series analysis by pretrained lm
Reference 42
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Reference 1992
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ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data MetaNeRV: Meta Neural Representations for Videos with Spatial-Temporal Guidance
Reference 2006
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Reference 2011
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Observation 63f809b8-4228-4ec7-87ad-357a4925af0f · outbound
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Csdi: Conditional score- based diffusion models for probabilistic time series impu- tation
Reference 2012
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Observation c26ef8b0-a3f5-42ee-97c3-423b391f7d58 · outbound
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Reference 2016
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Observation 5978027a-a0d0-4037-8f2b-5e57895c98db · outbound
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Attention beats linear for fast implicit neural representa- tion generation
Reference 2017
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ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Transformers as meta-learners for implicit neural repre- sentations
Reference 2018
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ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Time-Series Anomaly Detection with Implicit Neural Representation
Reference 2019
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Reference 2020
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Observation 8657160d-12b5-4079-9396-11bf9cf9384f · outbound
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Nrtsi: Non-recurrent time series imputation
Reference 2021
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Observation ceea3a79-dc6d-45b3-9104-1150378fb552 · outbound
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data An introduction to ker- nel and nearest-neighbor nonparametric regression
Reference 2022
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Observation 1c65bdf9-f302-4884-8b21-a87d3c668618 · outbound
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Reference 2023
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Observation 2fa216e9-a2cc-4ed2-9598-f18506427128 · outbound
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Reference 2024
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Observation 7662bb53-068d-4ab8-88ff-02e855cd3d72 · outbound
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data Kale, Greg Ver Steeg, and Aram Galstyan
Reference 2025
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No inbound Pith citation observations are available.