Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T14:20:35.937849Z
Paper Citation Record · LEDGER
Unsupervised learning using topological data augmentation
As of 16 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 1 inbound Pith citation observation for arXiv:1908.03469.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T14:20:35.902647Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-14T14:20:35.967905Z
Reference resolution
13 of 13 outbound references displayed
- verified exact0
- verified fuzzy9
- unresolved3
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 32f07fdc-09c4-4add-a5dc-a22393c12e47 · outbound
This paper cites Unsupervised learning using topological data augmentation.
Unsupervised learning using topological data augmentation Unsupervised learning using topological data augmentation
Reference 1
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-14T14:20:35.973345Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 401a1308-ec63-4afa-860e-7a51a40865ae · outbound
This paper cites an unresolved cited work.
Unsupervised learning using topological data augmentation Unresolved cited work
Reference 2
- Resolution
- unresolved
- raw_fallback, observed 2026-08-14T14:20:36.071459Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1bc8b7d6-7a1f-41eb-bfa6-4316ea76ef51 · outbound
This paper cites ω = 1 hx hy k FIG.
Unsupervised learning using topological data augmentation ω = 1 hx hy k FIG
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T14:20:36.063223Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 190c47e3-0aad-46be-b850-c2d079a43b41 · outbound
This paper cites 2, with known winding num- bers ω = 0 and ω = 1.
Unsupervised learning using topological data augmentation 2, with known winding num- bers ω = 0 and ω = 1
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T14:20:36.053634Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f0a5dc89-c714-434c-944d-5236d02c3419 · outbound
This paper cites an unresolved cited work.
Unsupervised learning using topological data augmentation Unresolved cited work
Reference 5
- Resolution
- unresolved
- raw_fallback, observed 2026-08-14T14:20:36.045646Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 97b23e05-166f-4d95-b0d2-f88ec1c9ad56 · outbound
This paper cites 4 we plot the network’s output y evaluated on the test dataset after training for 500 epochs with learning rate 10 −4 and for 500 epochs with learning rate 10−5.
Unsupervised learning using topological data augmentation 4 we plot the network’s output y evaluated on the test dataset after training for 500 epochs with learning rate 10 −4 and for 500 epochs with learning rate 10−5
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T14:20:36.036958Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ee784c4c-ffed-4bd4-ad61-d52abbd71563 · outbound
This paper cites We now show that it is in fact not necessary for the classification to know the winding number of the non-trivial parent to get the topological classification.
Unsupervised learning using topological data augmentation We now show that it is in fact not necessary for the classification to know the winding number of the non-trivial parent to get the topological classification
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T14:20:36.028275Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a5d4103b-f11f-4ae7-b2c3-8f0699ce2881 · outbound
This paper cites A few examples, corre- sponding to random Hamiltonians, are shown in Fig.
Unsupervised learning using topological data augmentation A few examples, corre- sponding to random Hamiltonians, are shown in Fig
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T14:20:36.018754Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d3d95501-f3bf-4587-874e-2ed8e053b442 · outbound
This paper cites II A we here develop a scheme for finding topologically nontrivial band insulators belonging to symmetry class A in 2d.
Unsupervised learning using topological data augmentation II A we here develop a scheme for finding topologically nontrivial band insulators belonging to symmetry class A in 2d
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T14:20:36.009860Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 00581f60-8289-4d13-b33d-3f12be210e77 · outbound
This paper cites 8: Examples of 2d band insulators: 1.
Unsupervised learning using topological data augmentation 8: Examples of 2d band insulators: 1
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T14:20:36.001001Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b27e7bd2-befa-4776-91d4-499885962715 · outbound
This paper cites unique correspondence with continuous ones via an in- terpolation procedure schematically illustrated in Fig.
Unsupervised learning using topological data augmentation unique correspondence with continuous ones via an in- terpolation procedure schematically illustrated in Fig
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T14:20:35.991602Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 12716305-b53f-4134-a4a7-13c45dd314df · outbound
This paper cites II A but now extended to 2d layered input as shown in Fig.
Unsupervised learning using topological data augmentation II A but now extended to 2d layered input as shown in Fig
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T14:20:35.982583Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 97d80287-3b0b-49dc-8032-fb2ff80b089f · outbound
This paper cites Discovering physical concepts with neural networks.
Unsupervised learning using topological data augmentation Discovering physical concepts with neural networks
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T14:20:35.937849Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation 32f07fdc-09c4-4add-a5dc-a22393c12e47 · inbound
Unsupervised learning using topological data augmentation cites this paper.
Unsupervised learning using topological data augmentation Unsupervised learning using topological data augmentation
Reference 1
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-14T14:20:35.973345Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.