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Paper Citation Record · LEDGER

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints

As of 22 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2605.24031.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2605.24031 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T16:49:34.205648Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

  • verified exact5
  • verified fuzzy29
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 987c5c3e-d4bc-42f8-8a67-816e8c87be47 · outbound

This paper cites Deep smoothing of the implied volatility surface.arXiv preprint arXiv:2004.11015, 2020.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Deep smoothing of the implied volatility surface.arXiv preprint arXiv:2004.11015, 2020

Reference 1

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arxiv_id, observed 2026-06-30T16:54:58.677790Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation dae76d3b-ed69-4add-9572-d5f30c0e764c · outbound

This paper cites The little Heston trap.Wilmott Magazine, pages 83–92, 2007.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints The little Heston trap.Wilmott Magazine, pages 83–92, 2007

Reference 2

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:fc4ca6e7296b8dc00450a06516cd25c1707e3ba04b7cb88d4f5e55954f46ecaa

Observation 92cd33e4-cd1f-4f14-84b9-cd2f765afe66 · outbound

This paper cites Layer Normalization.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Layer Normalization

Reference 3

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local_arxiv, observed 2026-06-30T16:54:58.688525Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:9a329ad25bb91238dd8fbc5fcd00d2f81b6efc40dedb67c5fbdbc7936ab2bc35

Observation 20138d71-87d9-4663-ab6e-4fd103ef6477 · outbound

This paper cites Deep calibration of rough stochastic volatil- ity models.Quantitative Finance, 19(1):71–86, 2019.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Deep calibration of rough stochastic volatil- ity models.Quantitative Finance, 19(1):71–86, 2019

Reference 4

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raw_fallback, observed 2026-07-08T12:14:52.190672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:016a5c1180f70cce23280fb106c4366b886d1e9e0943fbea272f3ec3df56c989

Observation 1e8cb8dd-fed4-47f6-809f-514013a8ca69 · outbound

This paper cites Variational autoencoders: A hands-off approach to volatility.The Journal of Finan- cial Data Science, 4(2):125–138, 2022.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Variational autoencoders: A hands-off approach to volatility.The Journal of Finan- cial Data Science, 4(2):125–138, 2022

Reference 5

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raw_fallback, observed 2026-07-08T12:14:52.179810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:384b08dde6b5be4ae2b5c609447c36383bd5a12d7e9d2c2a0316366b95acffa8

Observation 88f418e1-b941-42c5-9c8e-496738fa7e4c · outbound

This paper cites Image inpainting.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Image inpainting

Reference 6

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:3a730795cee0e3980e370fee913a8a97781732b3aacf657300436a24c59661fa

Observation dc2f9f29-645e-4c92-8a85-38cf61c9a294 · outbound

This paper cites The pricing of commodity contracts.Journal of Financial Economics, 3(1-2):167–179, 1976.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints The pricing of commodity contracts.Journal of Financial Economics, 3(1-2):167–179, 1976

Reference 7

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source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:595f3d6f091f18f36c1ed444f135aade5c22523655edf403be1b03637c425696

Observation 1452eaf2-64c4-4039-a231-3550481c9c07 · outbound

This paper cites The pricing of options and corporate liabilities.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints The pricing of options and corporate liabilities

Reference 8

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source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:1babc68f2db99078614a4c554d124eb21330bc4c91c9b0aea7fa1bbf237f8c5e

Observation 04d19e32-44e2-4f50-963f-6df2fcb4da1f · outbound

This paper cites Breeden and Robert H.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Breeden and Robert H

Reference 9

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Observation 0236f7c1-a30b-42c4-9653-ac2e5919e4e1 · outbound

This paper cites Byrd, Peihuang Lu, Jorge Nocedal, and Ciyou Zhu.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Byrd, Peihuang Lu, Jorge Nocedal, and Ciyou Zhu

Reference 10

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raw_fallback, observed 2026-07-08T12:14:52.204387Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:7e7afe4b0949fc6f4bcec8730f4bdac6de0c9314904174fb72978713e89ed166

Observation 9b0b9473-ce1f-4211-a14b-3e3e47b7daa5 · outbound

This paper cites Christie.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Christie

Reference 11

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source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:e3abb1eaec2faefe83f6f91030bbee0ae37d189fe0f1880a97f4722e220dd6bc

Observation ea535a32-7b72-45c2-9516-3a974fbd2679 · outbound

This paper cites Fast and accurate deep network learning by exponential linear units (ELUs).

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Fast and accurate deep network learning by exponential linear units (ELUs)

Reference 12

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:7a74e57d4287f262335edf41f8ba29c4ea6d8506e4f4e43641fc24465a926980

Observation 2802cd9d-ac0a-4a4d-a727-81bfb726d876 · outbound

This paper cites BERT: Pre- training of deep bidirectional transformers for language understanding.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints BERT: Pre- training of deep bidirectional transformers for language understanding

Reference 13

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source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:b29eb1ba84c4faa9dbbde7bcf8d66a7a13bc48ac1a34eb71adc4da8ff1e2f45c

Observation 497f9037-5643-4d40-916c-da5c2a75e770 · outbound

This paper cites an unresolved cited work.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Unresolved cited work

Reference 14

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Observation 859eada2-bce4-4c8b-9fc6-0a324419bcde · outbound

This paper cites Historic options dataset: Spy, iwm, and qqq options 2008-2025, 2025.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Historic options dataset: Spy, iwm, and qqq options 2008-2025, 2025

Reference 15

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:4be220356edb892abc666b06c3543bf73bef3a3280bd4a21d4a45a809277b8cc

Observation 300a06c5-9b34-467d-9824-b67d2b9bd59c · outbound

This paper cites Wiley, 2011.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Wiley, 2011

Reference 16

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:3511b8a6fd465dcca4ca20cac8b44fee4d1680d689cccd516e57046bfad74dac

Observation 4d64084d-b8ef-4cd4-852e-d165d5aaadad · outbound

This paper cites Arbitrage-free SVI volatility surfaces.Quanti- tative Finance, 14(1):59–71, 2014.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Arbitrage-free SVI volatility surfaces.Quanti- tative Finance, 14(1):59–71, 2014

Reference 17

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Observation ec488685-f6a1-463f-90ad-b6d0375eab18 · outbound

This paper cites Gil-Pelaez.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Gil-Pelaez

Reference 18

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Observation edc1c65b-2c16-40b8-8d17-3fa9c7add560 · outbound

This paper cites Hagan, Deep Kumar, Andrew S.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Hagan, Deep Kumar, Andrew S

Reference 19

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:9cad2e2387ba5f01fc618d03a63fd2eb8df4fab98a186df98f5f2863cbe4bd47

Observation 4caca5e4-af76-49fc-b310-a7c1d6848a96 · outbound

This paper cites Michael Harrison and David M.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Michael Harrison and David M

Reference 20

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Observation 7edab3fb-1da8-4cef-85c5-97356dc10608 · outbound

This paper cites Masked autoencoders are scalable vision learners.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Masked autoencoders are scalable vision learners

Reference 21

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source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:61781f68daca5224e5ffcd5f99a7cf0490f885cf97f4824c39de52ae6c7174c8

Observation d4109516-1b23-4b72-803e-b814c5434f32 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Gaussian Error Linear Units (GELUs)

Reference 22

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local_arxiv, observed 2026-06-30T16:54:58.692481Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:922d0f3ba6f3a0c5ff526e3dd69ece69541d99a7d5e7d961984ea1605e726ffd

Observation 102c52db-0657-43e4-ae66-78d587a3df38 · outbound

This paper cites an unresolved cited work.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Unresolved cited work

Reference 23

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:a08b8c9114985a2a99212aac82804d14d3318c0589b9ec8c6ca4db349ef4781f

Observation bce68bc5-3eef-4275-bbc2-494223db6fdf · outbound

This paper cites Multilayer feedforward networks are universal approximators.Neural Networks, 2(5):359–366.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Multilayer feedforward networks are universal approximators.Neural Networks, 2(5):359–366

Reference 24

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:fb00bda3cdbfc5fd23efca4732e3212e1723bdad31c54be7d21590f98efd977d

Observation 9c80c10e-0b1f-499d-ab30-3758ee8821ed · outbound

This paper cites Deep learning volatility: A deep neural network perspective on pricing and calibration in (rough) volatility mod- els.Quantitative Finance, 21(1):11–27, 2021.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Deep learning volatility: A deep neural network perspective on pricing and calibration in (rough) volatility mod- els.Quantitative Finance, 21(1):11–27, 2021

Reference 25

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:b378c8fdc1918d9f328cbda4e5f1288f3e7d022297bc2e52adcdc41fd0dcb3f0

Observation 6692291e-498f-417b-bb54-19cebb73d0ca · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Batch normalization: Accelerating deep network training by reducing internal covariate shift

Reference 26

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:1a719791ea1396e7f5305418f41a000047082ab1ce4e0fd435419279b0be253b

Observation d64abbc7-9350-43cb-a912-bcb68435a253 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Adam: A Method for Stochastic Optimization

Reference 27

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local_arxiv, observed 2026-06-30T16:54:58.684672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:83dfd2b488f80ab36111ee5adec5751e5df67c5e7f209dcc520e1dde487e754c

Observation 3cae4e20-cdbb-42f2-b367-039bebd480b4 · outbound

This paper cites Auto-Encoding Variational Bayes.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Auto-Encoding Variational Bayes

Reference 28

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local_arxiv, observed 2026-06-30T16:54:58.680923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:ac3cd9181626f0895db591699cdc0d492e2b4bb1187d51a2ab4bcdc33b27b725

Observation dcd9860c-e93c-4ec8-a913-890ab38c5cc4 · outbound

This paper cites Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278– 2324, 1998.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278– 2324, 1998

Reference 29

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:dc240129c60c7c854c1e68eef0af7c5831a0da663b78af2984a152500d050deb

Observation af53dacd-a58a-4cf3-b354-0cef703021dc · outbound

This paper cites an unresolved cited work.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Unresolved cited work

Reference 30

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:16adac98171810b0078a08235e4624009ae3f24f2cbe2bc6dbb7f56fc4640043

Observation 0378f6a7-fb5c-4a72-97ee-7523350e0439 · outbound

This paper cites an unresolved cited work.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Unresolved cited work

Reference 31

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:8efb57e55dfb424ef4891362b87d12dcd95ae9e06318dbc85f23d625dd47d8f1

Observation 52c16b99-1458-4ddb-9edc-62ec95724202 · outbound

This paper cites Ning, Sebastian Jaimungal, Xiaorong Zhang, and Maxime Bergeron.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Ning, Sebastian Jaimungal, Xiaorong Zhang, and Maxime Bergeron

Reference 32

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raw_fallback, observed 2026-07-08T12:14:52.175420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:4d8b880d5c271d96b14c5e6d05fad1dbe9a5529f36825323e9b8f24e5b2ccd51

Observation 52aa6ac2-df6a-4038-926e-8807872155d6 · outbound

This paper cites Variational autoencoders for completing the volatility surfaces.Journal of Risk and Financial Management, 18(5):239, 2025.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Variational autoencoders for completing the volatility surfaces.Journal of Risk and Financial Management, 18(5):239, 2025

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:5d332cbe4eb97dccb4d2ef9a0b17ba30762b2bf9895debc7cb53ba05f9fa4994

Observation b8d56b93-4353-4df6-a1d8-5968d0469cee · outbound

This paper cites Py- Torch: An imperative style, high-performance deep learning library.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Py- Torch: An imperative style, high-performance deep learning library

Reference 34

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verified fuzzy
raw_fallback, observed 2026-07-08T12:14:52.195381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:0ee3f565027b6b867479c6507a9080c98610d1892fe0bb36546a62a3893be67c

Observation bc59d1c5-0513-4be1-869e-a58320da5055 · outbound

This paper cites an unresolved cited work.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-07-08T12:14:52.208947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:eca7db46efe4659d2e35e52b0ba72ef8513e0d28e752e20e1c5f020577f24dc9

Observation f8c600da-1049-4631-a495-60f2fce7e2fb · outbound

This paper cites U-Net: Convolutional networks for biomedical image segmentation.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints U-Net: Convolutional networks for biomedical image segmentation

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T12:14:52.198080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:da38b62b0e01ee7b118a75beb2d3edf3f2f7ca207ae5a410579e0ab3bf52be22

Observation 7ed064b8-bd23-4aea-a993-5ec3d49175de · outbound

This paper cites Dropout: A simple way to prevent neural networks from overfitting.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Dropout: A simple way to prevent neural networks from overfitting

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T12:14:52.200342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:885575463dcb18b87dfb0d5189acc059919e77bfcf6d028043f31c96688d2e0a

Observation 40bb730d-3a38-404b-b05a-15feb4b5e7d8 · outbound

This paper cites Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T12:14:52.192800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:2a0572e19702e18a02b3688f1226953a8379cae48bfcab49cb2d9b8750a50b91

Observation 70fdd1ae-e365-4f86-9978-e9e0df9eedd0 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T12:14:52.173358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:8cc684bc60aa542264778734510da5f6bb7a09ce54a208c604ee38a9c707b15c

Observation 0dc53b7d-02cd-4b3c-98c8-f46983d963ca · outbound

This paper cites Meta-learning neural process for im- plied volatility surfaces with SABR-induced priors.arXiv preprint arXiv:2509.11928, 2025.

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints Meta-learning neural process for im- plied volatility surfaces with SABR-induced priors.arXiv preprint arXiv:2509.11928, 2025

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-06-30T16:54:58.696541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T16:49:34.205648Z digest=sha256:61c863d0eefd5397811d6e08838d6f0ae9cc38699ccf9744785b2543c08eabd4

Pith citing papers

No inbound Pith citation observations are available.