Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T14:45:20.169177Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 100 of 148 outbound references and 6 inbound Pith citation observations for arXiv:2507.17912.
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 2026-08-06T14:45:20.169177Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-03T23:41:26.610335Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T02:59:25.684114Z
100 of 148 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation bfc5347a-f962-486b-9929-d55c13e25846 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Highly accurate protein structure prediction with alphafold.Nature, 596(7873):583–589, 2021
Reference 1
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Observation e5ebd3ff-4d54-4f83-a452-db83718f8024 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning The nobel prize in physics 2024, 2024
Reference 2
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Observation f44f0e32-7e10-4586-a091-eef3ac6bf203 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning The nobel prize in chemistry 2024, 2024
Reference 3
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Observation b0385796-8160-412b-9f41-650a8c2ba462 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 4
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Observation 37dfd05a-3116-462d-b517-fbe62d179bdf · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Engel and C
Reference 5
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Observation 8b8cd7c5-dc2a-45b9-a43c-1ee168c2d0df · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning The space of interactions in neural network models.Journal of Physics A: Mathematical and General, 21(1):257, jan 1988
Reference 6
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Observation 2b1e4701-bcbe-494a-9299-4f165017c1b6 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Sompolinsky, N
Reference 7
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Observation a8c0c886-5670-454a-9ef8-61b9b736c54b · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 8
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Observation a0279efb-2827-4499-9abe-e36241e25194 · outbound
Reference 9
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Observation b27c188e-4b0e-4923-8982-3a1cd25e8e19 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Statistical physics, Bayesian inference and neural information processing
Reference 10
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Observation 5ad0389b-dd9e-4a88-8fb1-bf9954d1ab6b · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Vapnik.Statistical Learning Theory
Reference 11
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Observation 47f21556-749d-48a6-bfc7-7a7a6296aec7 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Neuralnetworksandphysicalsystemswithemergentcollectivecomputationalabilities
Reference 12
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Observation 44c28e7f-d0b5-4fd1-b1b9-fe9752f7dc40 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 13
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Observation c4076c62-7239-461c-bf4b-58a760a485c5 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 14
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Observation dea89ee6-095d-4bf7-8317-79aec33557e3 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 15
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Observation 4e3f09fb-61d6-49fa-9db8-12446db06ed3 · outbound
Reference 16
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Observation e7775a9b-f454-479f-b689-5d2e4e396b27 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning A brief prehistory of double descent
Reference 17
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Observation d21c80d5-8a53-4ca8-b485-3141223593eb · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 18
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Observation 36f74a5d-01ce-4e36-bc71-53861855569b · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Roberts, Sho Yaida, and Boris Hanin
Reference 19
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Observation 36e99f64-a6f8-4a78-b9af-ed96f5c1dc2c · outbound
Reference 20
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Observation 8712ea51-31b1-436f-a890-edb0efc380fd · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 21
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Observation ed7d2c52-8bfe-47fc-bc6b-b75babb86018 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Haussler, M
Reference 22
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Observation 95958104-a5f0-429c-b505-2eff77d4eb27 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data
Reference 23
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Observation ca45a118-8f9f-4294-82eb-3949c7ddac00 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Post-mortem on a deep learning contest: a Simpson's paradox and the complementary roles of scale metrics versus shape metrics
Reference 24
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Observation d5c3de3c-740e-494d-a605-30e6beb52e5c · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 25
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Observation c229e3a8-85a3-45f0-a014-0adbce16a01b · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 26
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Observation c61174b1-5816-4df9-8c82-524a213a17d7 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data
Reference 27
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Observation 4627ab2a-0e2a-4ac7-bf26-2205255a84c3 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 28
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Observation 5fd388a6-e602-4f00-9767-0b2ea0ffec28 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Temperature balancing, layer-wise weight analysis, and neural network training
Reference 29
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Observation fd9c7752-120c-4974-b668-b8969041dfd3 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Mahoney, and Yaoqing Yang
Reference 30
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Observation ec9c16df-5a33-43c1-8fe2-2926fb765c77 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Hans Bethe and the theory of nuclear matter.Physics Today, 58(10):58, 2005
Reference 31
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Observation a9fe06ec-5587-4827-85a4-c601a8c3fe8a · outbound
Reference 32
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Observation b6a7a512-6341-4419-90d5-af187c1d48c6 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning On closed shells in nuclei
Reference 33
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Observation a16a2550-cf99-4b37-9379-22ed315d2ae3 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning magic numbers
Reference 34
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Observation de1304b9-c5d0-49d6-a753-91c7537379b3 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Characteristic vectors of bordered matrices with infinite dimensions
Reference 35
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Observation b7738a13-2d6c-4966-a970-2db8ec58c248 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 36
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Observation e3e17c80-a51b-4b52-8e3b-f9398c6c2d2e · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 37
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Observation 0d80048a-5567-4a09-be4c-29d8d326647b · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 38
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Observation 89b74c2b-93ea-4bc7-ad82-3b8534bcb04f · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Sener and Klaus Schulten
Reference 39
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Observation 89c34f06-b706-49ce-bad7-5a744857a363 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Gallucio, J.-P
Reference 40
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Observation 23e4435f-17fd-443d-aa23-07a7751a25b1 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Cherrier, D
Reference 41
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Observation 90731596-0314-4966-91ae-293d2977e2e8 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 42
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Observation 229dd47e-01c5-4382-80d4-1845b0a1384b · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 43
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Observation fd347550-9dde-4e42-ad27-cb10b840d5de · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 44
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SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 45
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SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 46
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Observation 6417f48b-995d-4cc9-a146-c09abf0bf65f · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Theoretical studies of enzymic reactions: dielectric, electrostatic and steric stabilization of the carbonium ion in the reaction of lysozyme
Reference 47
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Observation a30f1f46-90da-4dd4-926a-439b2e73ebeb · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Chapter 21 - semiempirical quantum-chemical methods in computational chemistry
Reference 48
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Observation 2d3d2abc-1f59-4fe6-af8f-610fd9c562d5 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 49
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Observation ee02a106-e8a3-483d-b488-a02ca20e3956 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 50
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SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 51
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Observation ed6588f3-5490-43eb-a7ec-0580b4c11df3 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Martin and Karl F
Reference 52
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SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 53
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SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 54
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Observation 26cfb57d-2334-47a4-9b20-5583d218760f · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Martin and Robert R
Reference 55
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Observation 9ca6f8f8-5e37-4da4-ad27-199eaf925472 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning The nobel prize in physics 1982: Kenneth g
Reference 56
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Observation 876312fb-a238-4389-bf7a-f7578897a5a9 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 57
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Observation 196168bf-af09-41ae-84f2-3d8d460490e1 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Improving language under- standing by generative pre-training.OpenAI, 2018
Reference 58
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Observation 15ec5638-2e4b-4a9e-b40d-96256617b0c4 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Rapid calculation of side chain packing and free energy with applications to protein molecular dynamics
Reference 59
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SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 60
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SETOL: A Semi-Empirical Theory of (Deep) Learning Deep Neural Networks as Gaussian Processes
Reference 61
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SETOL: A Semi-Empirical Theory of (Deep) Learning Tensor Programs III: Neural Matrix Laws
Reference 62
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SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 63
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SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 64
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SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 65
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Observation 2f4454a4-00b4-41b0-b764-f114a566aad8 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Bryngelson and Peter G
Reference 66
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SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 67
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SETOL: A Semi-Empirical Theory of (Deep) Learning Clauset, C
Reference 68
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Observation 24edc05c-e1e2-46ab-9968-757a84471616 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Alstott, E
Reference 69
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Observation 1f9d3aaf-3bf9-4c6d-ae0e-8a0a26e498d3 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Random matrix analysis of deep neural network weight matrices.Physical Review E, 106(5):054124, 2022
Reference 70
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SETOL: A Semi-Empirical Theory of (Deep) Learning Bouchaud and M
Reference 71
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SETOL: A Semi-Empirical Theory of (Deep) Learning Edelman and Y
Reference 72
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SETOL: A Semi-Empirical Theory of (Deep) Learning Cambridge University Press, 2020
Reference 73
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Observation 50e7bfe7-9e37-431f-b619-7e3d59123937 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Learning spectral clustering, with application to speech separation
Reference 74
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Observation 74f4d436-48a7-4467-8cfb-722e32c6771d · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning The eigenvalues and eigenvectors of finite, low rank perturbations of large random matrices.Advances in Mathematics, 227(1):494–521, 2011
Reference 75
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Observation 586bdfb9-08a5-4e38-a7fc-07cd226a6aab · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Oxford University Press, Oxford, UK, 1997
Reference 76
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SETOL: A Semi-Empirical Theory of (Deep) Learning Noisedressingoffinancialcorrelationmatrices
Reference 78
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Reference 79
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Observation 11e345e0-1ca1-497c-828d-24c5a568a635 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Taxonomizing local versus global structure in neural network loss landscapes
Reference 80
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Observation 73cdb024-2bcd-4ca9-a7c3-34f95977c62d · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Heavy-Tailed Universality Predicts Trends in Test Accuracies for Very Large Pre-Trained Deep Neural Networks
Reference 81
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SETOL: A Semi-Empirical Theory of (Deep) Learning Sompolinsky, N
Reference 82
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Reference 83
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Reference 84
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Reference 85
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SETOL: A Semi-Empirical Theory of (Deep) Learning Dragon-kings, black swans and the prediction of crises, 2009
Reference 86
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Observation 732a57b7-ec68-467a-93f7-8c9348347a2c · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning The Heavy-Tail Phenomenon in SGD
Reference 87
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SETOL: A Semi-Empirical Theory of (Deep) Learning Nice: Noise injection and clamping estimation for neural network quantization.Mathematics, 9(17):2144, 2021
Reference 88
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SETOL: A Semi-Empirical Theory of (Deep) Learning PACT: Parameterized Clipping Activation for Quantized Neural Networks
Reference 89
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Reference 90
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Reference 92
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SETOL: A Semi-Empirical Theory of (Deep) Learning Martin and Karl F
Reference 94
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Reference 95
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Reference 96
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Observation 89432170-7e74-41ea-8da4-569c7984f32d · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Training Compute-Optimal Large Language Models
Reference 97
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Observation a2255ed7-13bf-4a0d-a204-d7679aa664d0 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Unresolved cited work
Reference 98
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Observation bbbce530-0728-4de1-a2d8-1dfe419428fe · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Teacher-student architecture for knowledge distillation: A survey, 2023
Reference 99
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Observation ccfa045d-0a7a-4eae-8a82-7ba39c71aaf3 · outbound
SETOL: A Semi-Empirical Theory of (Deep) Learning Vallet, J.-G
Reference 100
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Observation 4980da65-f130-4ad1-a403-509838d2bc0e · outbound
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Reference 101
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Detecting overfitting in Neural Networks during long-horizon grokking using Random Matrix Theory SETOL: A Semi-Empirical Theory of (Deep) Learning
Reference 14
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Detecting overfitting in Neural Networks during long-horizon grokking using Random Matrix Theory SETOL: A Semi-Empirical Theory of (Deep) Learning
Reference 14
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Reference 298
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Fast Generalization after Interpolation via Critically Damped Momentum Optimization SETOL: A Semi-Empirical Theory of (Deep) Learning
Reference 56
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Observation 35c31516-5a2d-4152-951b-d1a54d05aa01 · inbound
Patnaik-Pearson intrinsic dimension for internal representations of neural networks SETOL: A Semi-Empirical Theory of (Deep) Learning
Reference 22
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Observation 1e2ab913-6ec1-464f-ac2c-69eff9486ca9 · inbound
Patnaik-Pearson intrinsic dimension for internal representations of neural networks SETOL: A Semi-Empirical Theory of (Deep) Learning
Reference 23
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