Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:30:52.377104Z
Paper Citation Record · LEDGER
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform
As of 8 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2506.05090.
A citation records a reference. It does not transfer a finding from one paper to another.
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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
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Source: cited_works
Reference resolution
56 of 56 outbound references displayed
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation d3de4659-b544-4e83-a961-ed6e7f32e531 · outbound
This paper cites an unresolved cited work.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Unresolved cited work
Reference 1
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Observation f9e53013-5500-49dd-b355-bc08726f83f1 · outbound
This paper cites The filters are parameterized as ˆψjl(⃗k) =F jl(⃗k, j), whereFjl is a neu- ral network that maps Fourier-space coordinates ⃗kto filter values.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform The filters are parameterized as ˆψjl(⃗k) =F jl(⃗k, j), whereFjl is a neu- ral network that maps Fourier-space coordinates ⃗kto filter values
Reference 2
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Observation 36c6ab30-fec3-47b1-94aa-986efac3bcb7 · outbound
This paper cites an unresolved cited work.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Unresolved cited work
Reference 3
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Observation 4da06157-f156-4987-8c43-4a0fdae824da · outbound
This paper cites an unresolved cited work.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Unresolved cited work
Reference 4
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Observation b3b31c9e-669b-4944-ac0b-5ed18ed3412e · outbound
This paper cites an unresolved cited work.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Unresolved cited work
Reference 5
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Observation 5b1a3a3f-f026-425b-a5b0-b2b10c0c209e · outbound
This paper cites an unresolved cited work.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Unresolved cited work
Reference 6
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Observation cd3d8bcf-8d5e-4130-963f-c27625ec8654 · outbound
This paper cites To treat each summary statistic equally in the downstream analysis, we choose to pre-train the NFST and CNN summary statistics and freeze their trainable components.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform To treat each summary statistic equally in the downstream analysis, we choose to pre-train the NFST and CNN summary statistics and freeze their trainable components
Reference 7
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Observation 28fa82de-f630-4fb2-a71e-7c872c4439a1 · outbound
This paper cites We use the same MLP model and training setup as with pre-training, but in- stead train for 2000 epochs with a learning rate of 10−4.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform We use the same MLP model and training setup as with pre-training, but in- stead train for 2000 epochs with a learning rate of 10−4
Reference 8
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Observation b97df8fe-a2e6-4ec4-9b76-388e2b3b8027 · outbound
This paper cites To cap- ture these, we instead use Neural Posterior Estimation (NPE).
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform To cap- ture these, we instead use Neural Posterior Estimation (NPE)
Reference 9
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Observation 7cfbcee9-a410-43cd-92b5-5e82d9c6d7e1 · outbound
This paper cites We expand upon work from [40], which visualizes the information that an arbitrary summary statistic captures from a tar- get field.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform We expand upon work from [40], which visualizes the information that an arbitrary summary statistic captures from a tar- get field
Reference 10
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Observation e82bfc94-1350-4e9b-af5e-37b139eaf88d · outbound
This paper cites an unresolved cited work.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Unresolved cited work
Reference 11
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Observation c5da7334-0a4a-472e-9076-b52c2da41673 · outbound
This paper cites The Hubble constant tension: current status and future perspectives through new cosmological probes.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform The Hubble constant tension: current status and future perspectives through new cosmological probes
Reference 12
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Observation eb9d74d1-40e7-4d0a-b5f1-425bb295a2b7 · outbound
This paper cites The Dark Energy Survey Supernova Program: Investigating Beyond-$\Lambda$CDM.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform The Dark Energy Survey Supernova Program: Investigating Beyond-$\Lambda$CDM
Reference 13
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Source-reported events for the cited work
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Observation 83df98df-6921-4f0a-b3f2-c0f9508216fd · outbound
This paper cites The Dark Energy Survey: Cosmology Results With ~1500 New High-redshift Type Ia Supernovae Using The Full 5-year Dataset.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform The Dark Energy Survey: Cosmology Results With ~1500 New High-redshift Type Ia Supernovae Using The Full 5-year Dataset
Reference 14
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Source-reported events for the cited work
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Observation 61d4f142-fb93-436c-a141-f2705a57f9aa · outbound
This paper cites The Ups and Downs of Early Dark Energy solutions to the Hubble tension: a review of models, hints and constraints circa 2023.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform The Ups and Downs of Early Dark Energy solutions to the Hubble tension: a review of models, hints and constraints circa 2023
Reference 15
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Source-reported events for the cited work
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Observation e54be5ff-39d6-4d77-82b6-7df891240b91 · outbound
This paper cites DESI 2024 VI: Cosmological Constraints from the Measurements of Baryon Acoustic Oscillations.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform DESI 2024 VI: Cosmological Constraints from the Measurements of Baryon Acoustic Oscillations
Reference 16
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Source-reported events for the cited work
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Observation 88cafb84-30f2-4bd0-a3ab-14796a16bf2d · outbound
This paper cites Full-Shape analysis of the power spectrum and bispectrum of DESI DR1 LRG and QSO samples.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Full-Shape analysis of the power spectrum and bispectrum of DESI DR1 LRG and QSO samples
Reference 17
- Resolution
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Observation effe9f74-660f-417c-a0e7-32f592f185a9 · outbound
This paper cites Secco, S.
Reference 18
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Source-reported events for the cited work
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Observation a8b55b24-d66e-47dc-a1ca-6cd803ab8145 · outbound
This paper cites Asgari, C.-A.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Asgari, C.-A
Reference 19
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Observation 9b3e0d4e-478f-4793-b52a-8f5c82074a12 · outbound
This paper cites Hamana, M.
Reference 20
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Observation 3c8b0211-3268-4f6a-aab8-65df40dd7af2 · outbound
This paper cites Abbott, M.
Reference 21
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Observation b7a2605c-0ddb-4384-9135-7cd9f9fba876 · outbound
This paper cites Heymans, T.
Reference 22
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Observation 74e4b3f8-d81e-43ce-bf4d-7c1dda764d3b · outbound
This paper cites Hyper Suprime-Cam Year 3 Results: Measurements of Clustering of SDSS-BOSS Galaxies, Galaxy-Galaxy Lensing and Cosmic Shear.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Hyper Suprime-Cam Year 3 Results: Measurements of Clustering of SDSS-BOSS Galaxies, Galaxy-Galaxy Lensing and Cosmic Shear
Reference 23
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Observation d98d95df-31c3-4511-b6b1-aab18b7e7089 · outbound
This paper cites Gil-Mar ´ ın, J.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Gil-Mar ´ ın, J
Reference 24
- Resolution
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Observation d5ba549c-8cad-4924-b9f3-f0459d714f9b · outbound
This paper cites Gil-Mar ´ ın, W.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Gil-Mar ´ ın, W
Reference 25
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Observation 1b1781d0-345f-4609-965a-57dc5c710780 · outbound
This paper cites Slepian, D.
Reference 26
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Observation ff328147-bd39-4448-a2ca-e05917326dc6 · outbound
This paper cites A First Detection of the Connected 4-Point Correlation Function of Galaxies Using the BOSS CMASS Sample.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform A First Detection of the Connected 4-Point Correlation Function of Galaxies Using the BOSS CMASS Sample
Reference 27
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Observation ccf7a586-87cd-4760-96b5-f8b490b911fe · outbound
This paper cites an unresolved cited work.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Unresolved cited work
Reference 28
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Observation a9083f7f-efb9-44b6-9c40-d2c42dc690b9 · outbound
This paper cites Bispectrum constraints on Primordial non-Gaussianities with the eBOSS DR16 quasars.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Bispectrum constraints on Primordial non-Gaussianities with the eBOSS DR16 quasars
Reference 29
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Observation 118ec41c-2961-42c5-a317-d082440b85a1 · outbound
This paper cites Cosmological information in the redshift-space bispectrum.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Cosmological information in the redshift-space bispectrum
Reference 30
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Observation b0702f62-3492-4bdf-9b56-04fcd7044312 · outbound
This paper cites an unresolved cited work.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Unresolved cited work
Reference 31
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Observation 8e1456c8-b046-472e-9ac9-7c4550c77c5c · outbound
This paper cites Window convolution of the galaxy clustering bispectrum.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Window convolution of the galaxy clustering bispectrum
Reference 32
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Observation b8c82a15-ca1d-4420-96d9-bbb407426fc2 · outbound
This paper cites Fluri, T.
Reference 33
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Observation 926219b0-7521-470e-8005-8cfe0454868f · outbound
This paper cites Dark Energy Survey Year 3 results: likelihood-free, simulation-based $w$CDM inference with neural compression of weak-lensing map statistics.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Dark Energy Survey Year 3 results: likelihood-free, simulation-based $w$CDM inference with neural compression of weak-lensing map statistics
Reference 34
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Reference 35
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Observation ae2537cc-cdde-4d4b-9037-99c9f8e13741 · outbound
This paper cites Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets
Reference 36
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Source-reported events for the cited work
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Observation 1602b60c-0c23-4137-9de2-d9a9298290cc · outbound
This paper cites Going Beyond the Galaxy Power Spectrum: an Analysis of BOSS Data with Wavelet Scattering Transforms.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Going Beyond the Galaxy Power Spectrum: an Analysis of BOSS Data with Wavelet Scattering Transforms
Reference 37
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Source-reported events for the cited work
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Observation d62ce171-5091-47ec-905f-c8019fef57b1 · outbound
This paper cites Valogiannis and C.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Valogiannis and C
Reference 38
- Resolution
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Observation ccee618c-e042-44a9-9a99-623d17d2c0b7 · outbound
This paper cites Precise Cosmological Constraints from BOSS Galaxy Clustering with a Simulation-Based Emulator of the Wavelet Scattering Transform.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Precise Cosmological Constraints from BOSS Galaxy Clustering with a Simulation-Based Emulator of the Wavelet Scattering Transform
Reference 39
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Observation 017362d6-cceb-470d-af62-4746b69ed0e5 · outbound
This paper cites Parametric Scattering Networks.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Parametric Scattering Networks
Reference 40
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Observation b671b983-e8dd-403b-a5c8-043980067d86 · outbound
This paper cites Khemani, M.
Reference 41
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 5427c9e9-1004-46a2-9251-684484be7a9f · outbound
This paper cites Unsupervised Searches for Cosmological Parity Violation: Improving Detection Power with the Neural Field Scattering Transform.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Unsupervised Searches for Cosmological Parity Violation: Improving Detection Power with the Neural Field Scattering Transform
Reference 42
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 65a06005-e8f9-46bc-a170-6f945f0c4647 · outbound
This paper cites Kuijken, C.
Reference 43
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d4e68146-5572-4f9d-89c8-ef147b31535e · outbound
This paper cites Mellier, Abdurro’uf, J.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Mellier, Abdurro’uf, J
Reference 44
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Source-reported events for the cited work
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Observation 9905fc9a-e7b0-4b98-adf9-7bdbde6aa2a1 · outbound
This paper cites LSST: from Science Drivers to Reference Design and Anticipated Data Products.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform LSST: from Science Drivers to Reference Design and Anticipated Data Products
Reference 45
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Unavailable: canonical work link unavailable.
Observation d58adcdd-6248-4eef-be98-62c8a38887ff · outbound
This paper cites Cheng and B.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Cheng and B
Reference 46
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Observation 34fd1812-58f6-4e2c-9884-9b89389034c2 · outbound
This paper cites Cranmer, J.
Reference 47
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Unavailable: canonical work link unavailable.
Observation ed02b5af-2d96-43b7-aaaa-b171d15087c7 · outbound
This paper cites Tejero-Cantero, J.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Tejero-Cantero, J
Reference 48
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Source-reported events for the cited work
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Observation 175ad0a2-2b94-4f76-bf47-5f2440e3061f · outbound
This paper cites Masked Autoregressive Flow for Density Estimation.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Masked Autoregressive Flow for Density Estimation
Reference 49
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Source-reported events for the cited work
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Observation d1bb8be1-3b56-4609-9d49-38834ab2f78b · outbound
This paper cites Benchmarking Simulation-Based Inference.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Benchmarking Simulation-Based Inference
Reference 50
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Source-reported events for the cited work
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Observation 560ac964-851e-41a9-a507-1a3399133d4d · outbound
This paper cites How to quantify fields or textures? A guide to the scattering transform.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform How to quantify fields or textures? A guide to the scattering transform
Reference 51
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Source-reported events for the cited work
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Observation 41e0bd44-c492-4f0b-8139-441a8b90398c · outbound
This paper cites Erhan, Y.
Reference 52
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Source-reported events for the cited work
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Observation fba45034-81e2-442e-97e1-5dd114c7d973 · outbound
This paper cites Visualizing and Understanding Convolutional Networks.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Visualizing and Understanding Convolutional Networks
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:30:52.139110Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e465f002-a482-4d2b-977c-cee9a211675d · outbound
This paper cites Understanding Neural Networks Through Deep Visualization.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Understanding Neural Networks Through Deep Visualization
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:30:52.213769Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 607ca053-265e-46a8-bb2e-940f13e7b4dc · outbound
This paper cites A Unified Approach to Interpreting Model Predictions.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform A Unified Approach to Interpreting Model Predictions
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:30:52.285492Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 423466b3-7fa2-4d65-9981-df4a963525db · outbound
This paper cites an unresolved cited work.
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform Unresolved cited work
Reference 56
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T10:30:53.512579Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Pith citing papers
No inbound Pith citation observations are available.