Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T12:21:21.982165Z
Paper Citation Record · LEDGER
Network Inversion and Its Applications
As of 13 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2411.17777.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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
Reference resolution
21 of 21 outbound references displayed
- verified exact0
- verified fuzzy19
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation fab51d1a-f833-45a8-b2c7-1e1f2e128cdc · outbound
This paper cites Autoinverse: Uncertainty aware inversion of neural networks, 2022.
Network Inversion and Its Applications Autoinverse: Uncertainty aware inversion of neural networks, 2022
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.286790Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation d429d6f5-4ae0-49fe-b770-e11cc8a666ec · outbound
This paper cites Recon- structing training data with informed adversaries.
Network Inversion and Its Applications Recon- structing training data with informed adversaries
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.272920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 7181b21f-e39b-4dc6-bfa3-e539b69d907e · outbound
This paper cites Reconstructing training data from multiclass neural networks, 2023.
Network Inversion and Its Applications Reconstructing training data from multiclass neural networks, 2023
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.259782Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 380c7950-33b8-4ef0-8ee0-58bdb667eb40 · outbound
This paper cites The mnist database of handwritten digit images for machine learning research.
Network Inversion and Its Applications The mnist database of handwritten digit images for machine learning research
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.245815Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 596418f1-af92-4b19-ad65-6a832094103d · outbound
This paper cites Reconstructing training data from trained neu- ral networks, 2022.
Network Inversion and Its Applications Reconstructing training data from trained neu- ral networks, 2022
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.231405Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 1031ea57-7bcb-44a3-85b9-8ca19b5b76b4 · outbound
This paper cites Batch normalization: Accelerating deep network training by reducing internal co- variate shift.
Network Inversion and Its Applications Batch normalization: Accelerating deep network training by reducing internal co- variate shift
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.217105Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 4cf8266f-8608-481a-b354-6a621a31a3fd · outbound
This paper cites Jensen, R.D.
Network Inversion and Its Applications Jensen, R.D
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.203805Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 89f54ae3-8d11-482c-87ae-720869f2ca88 · outbound
This paper cites Inversion of neural networks by gradient descent.
Network Inversion and Its Applications Inversion of neural networks by gradient descent
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.190485Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 635604df-f532-4d33-aa14-5023da736234 · outbound
This paper cites Cifar-10 (canadian institute for advanced research).
Network Inversion and Its Applications Cifar-10 (canadian institute for advanced research)
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.176572Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation e507abad-67d3-443e-8669-256f9eced196 · outbound
This paper cites Model inversion networks for model-based optimization.
Network Inversion and Its Applications Model inversion networks for model-based optimization
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.163244Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 5cf8d5d1-a34c-4792-b52d-00ac00c345cf · outbound
This paper cites Landscape learning for neural network inversion, 2022.
Network Inversion and Its Applications Landscape learning for neural network inversion, 2022
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:21:21.940524Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 494fd3a9-5ff3-493d-9d33-fc23afa6ab9b · outbound
This paper cites Convo- lutional sparse autoencoders for image classification.
Network Inversion and Its Applications Convo- lutional sparse autoencoders for image classification
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.140381Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation b2213d15-5a72-4ef7-a8f7-e78130568429 · outbound
This paper cites k-sparse autoencoders,.
Network Inversion and Its Applications k-sparse autoencoders,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.126038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 1ddeb11a-755d-4a2b-b82c-c90b72c45ee6 · outbound
This paper cites Saad and Donald C.
Network Inversion and Its Applications Saad and Donald C
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.111012Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 667975f1-1f10-48ac-b490-259e33c1a3a2 · outbound
This paper cites Dropout: A simple way to prevent neural networks from overfitting.
Network Inversion and Its Applications Dropout: A simple way to prevent neural networks from overfitting
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.096979Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 80d76793-5f8e-4e9b-a2cb-39f4b907322b · outbound
This paper cites Network inversion of binarised neural nets.
Network Inversion and Its Applications Network inversion of binarised neural nets
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.082740Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation dd75dc09-c91a-4b6a-9c20-d564c0713147 · outbound
This paper cites Reconstructing training data from model gradient, provably.
Network Inversion and Its Applications Reconstructing training data from model gradient, provably
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.068588Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation ac3b700f-d09e-4315-8e8a-35cd4487807e · outbound
This paper cites Neural network inversion beyond gradient de- scent.
Network Inversion and Its Applications Neural network inversion beyond gradient de- scent
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.054941Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 661e409c-a724-4551-9bfe-c71f3cfed507 · outbound
This paper cites Fashion- mnist: a novel image dataset for benchmarking machine learning algorithms, 2017.
Network Inversion and Its Applications Fashion- mnist: a novel image dataset for benchmarking machine learning algorithms, 2017
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:21:21.973865Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 25a69249-ac4d-4cd7-9edd-8ae925731f00 · outbound
This paper cites Empirical evaluation of rectified activations in convolutional network,.
Network Inversion and Its Applications Empirical evaluation of rectified activations in convolutional network,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.031064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 9810e389-31b5-47bd-b21b-75366b19a067 · outbound
This paper cites Neural network inversion in adversarial setting via back- ground knowledge alignment.
Network Inversion and Its Applications Neural network inversion in adversarial setting via back- ground knowledge alignment
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:21:22.016720Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Pith citing papers
No inbound Pith citation observations are available.