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Paper Citation Record · LEDGER

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework

As of 10 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2509.04875.

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

pith.paper-citation-record.v1
2509.04875 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T05:52:52.967806Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

49 of 49 outbound references displayed

  • verified exact1
  • verified fuzzy13
  • unresolved35
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ceeef588-f122-488c-aec5-c32e752791a3 · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation fbd2bfd9-c5ec-4d99-b424-9a9743a8d0e6 · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 2

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Observation d2071f25-b71d-4232-96a1-39abc4700546 · outbound

This paper cites & Feng, J.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework & Feng, J

Reference 3

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Observation ffe0fc0c-ca52-4b1a-a0bc-922bb122fe11 · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 4

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation a130dd1f-08c4-46f8-b436-16bae6c64b2f · outbound

This paper cites T., Gastegger, M., Tkatchenko, A., Müller, K.-R.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework T., Gastegger, M., Tkatchenko, A., Müller, K.-R

Reference 5

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Observation d281653a-0458-4eb7-9b52-e85f32133f16 · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 6

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3a50d1e9-104c-4619-a406-44a228681955 · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 31391045-d032-4cdf-a0de-675a5423740f · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 8

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ebb8ebc3-1c87-4266-9590-06c1888f0331 · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 9

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation c4d0c728-f464-4d83-8753-5b72586e42da · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 10

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Observation 225db154-7db8-4ef9-9146-52b537bcb89f · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 11

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation a10bc58e-3b3f-437b-8cd2-1004f987eed2 · outbound

This paper cites & Xiang, H.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework & Xiang, H

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 874f3723-9e47-47c0-bff9-53032231ba41 · outbound

This paper cites DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1880a535-3347-4caa-8d1e-688524cabe1d · outbound

This paper cites Learning local equivariant representations for quantum operators.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Learning local equivariant representations for quantum operators

Reference 14

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Observation 58715482-50c8-46dc-a331-517abab3c895 · outbound

This paper cites Relational inductive biases, deep learning, and graph networks.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Relational inductive biases, deep learning, and graph networks

Reference 15

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Observation 95374d4e-1702-450a-9fa3-8574b6e1188a · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Semi-Supervised Classification with Graph Convolutional Networks

Reference 17

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Observation 615397d0-2a82-4774-bcbf-51d0ead6c9a6 · outbound

This paper cites Graph Neural Networks: A Review of Methods and Applications.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Graph Neural Networks: A Review of Methods and Applications

Reference 18

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Observation 6cf18efa-fa4b-4a0c-8426-79078278d342 · outbound

This paper cites F., Vinyals, O.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework F., Vinyals, O

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation d7e63633-5952-4b8a-8876-ed5772f38bda · outbound

This paper cites Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs

Reference 20

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Observation 5d6a1b31-76bc-406e-b018-004cc9a019fb · outbound

This paper cites MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 21

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Observation 17bf52f7-ee73-4c97-ae20-36c9da78fbbc · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 56064f07-af6b-41de-ad67-9d4aac42a0cf · outbound

This paper cites Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products

Reference 23

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Observation 41915e1b-a3c6-47a3-92c5-2c6f2b311a35 · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 24

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Observation d13ebf9b-3ee5-4647-aea4-cdf184573dcd · outbound

This paper cites & Furthmüller, J.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework & Furthmüller, J

Reference 25

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Observation 893de2f5-cb9b-4b9c-86e7-903c4054b749 · outbound

This paper cites & Furthmüller, J.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework & Furthmüller, J

Reference 26

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3d1d1a2a-844d-4d7f-9e15-83940229f34e · outbound

This paper cites & Kino, H.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework & Kino, H

Reference 27

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ba7cdba2-1f98-4577-8645-2460f6b06624 · outbound

This paper cites Variationally optimized atomic orbitals for large -scale electronic structures.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Variationally optimized atomic orbitals for large -scale electronic structures

Reference 28

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3b42f22e-cb09-4a6d-b952-e3a6c862fc66 · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 29

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation d9a4d96e-cbbf-4ca4-98b2-345d909fbf7d · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation a6aea2fd-c1bb-43a0-8ef6-9b1650292f5f · outbound

This paper cites Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

Reference 31

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Observation 2be453e5-b070-4642-a264-88135ab83a9b · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation fe347a03-bb64-4fcd-89f3-1211120acaf0 · outbound

This paper cites Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics

Reference 33

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verified exact
local_arxiv, observed 2026-08-05T05:52:53.099635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 2ed14e63-0497-42c9-ae86-40242b3a55de · outbound

This paper cites https://pubs.aip.org/aapt/ajp/article- abstract/28/4/408/1036645/Group-Theory-and-Its-Application-to-the- Quantum?redirectedFrom=fulltext.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework https://pubs.aip.org/aapt/ajp/article- abstract/28/4/408/1036645/Group-Theory-and-Its-Application-to-the- Quantum?redirectedFrom=fulltext

Reference 34

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 29b18160-ab45-4245-84ac-142f8a1ba0d5 · outbound

This paper cites 3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework 3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3f9ac00b-a740-47c1-9ca0-4d949ca135e0 · outbound

This paper cites Precise control of the interlayer twist angle in large scale MoS2 homostructures.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Precise control of the interlayer twist angle in large scale MoS2 homostructures

Reference 37

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verified fuzzy
raw_fallback, observed 2026-08-05T05:52:53.335742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 978836c8-79cb-4264-be3a-b59d57ee7930 · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-05T05:52:53.322972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T05:52:52.922226Z digest=sha256:f94aa0b3eb2a8d2112744b62df36920a354828d0c74cf5a8a8fff49d900d0391

Observation 6175a4be-73e2-4405-af3b-848f86311dad · outbound

This paper cites & Koshino, M.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework & Koshino, M

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:52:53.310634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T05:52:52.925598Z digest=sha256:805520408a65e70a19b2bd40973e1293022ca790e2a62ad4a47882c0a7f7a0e6

Observation 2144267b-e3ad-476b-98b9-4396ac6ce9e7 · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-05T05:52:53.298790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T05:52:52.929074Z digest=sha256:d8c5ef64482621b78d8c20cd8e296962b0a87e55b2dab65b845d08ab71b23cf8

Observation 5275840d-38cf-41f3-95a7-c5c5850adb04 · outbound

This paper cites Electrical properties and applications of graphene, hexagonal boron nitride (h-BN), and graphene/h-BN heterostructures.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Electrical properties and applications of graphene, hexagonal boron nitride (h-BN), and graphene/h-BN heterostructures

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:52:53.286390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T05:52:52.932546Z digest=sha256:cd884f6675c4a976ef9ac3b1bcbdf08883c917b44e481969c7b3b689c0d96151

Observation e2e6db0c-2bac-49ef-8aeb-b41c36308d59 · outbound

This paper cites & Geng, W.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework & Geng, W

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:52:53.273811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T05:52:52.935832Z digest=sha256:5d96d72cd211d82a9786ccecf7a5f043d538fcdc74f14bce0aafef432ed11535

Observation 7e0c287b-e7f0-46ab-aa92-91350678117f · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-05T05:52:52.939233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:52:52.939233Z digest=sha256:1d1f3d4335628521b71b0a255c0d6fb1c6fc54efac4e9e6a1bde929415f1fc8c

Observation 8063310e-4234-4346-abff-88a08799dd6e · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-05T05:52:53.253305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T05:52:52.942824Z digest=sha256:282f2b9e0fef1cd0273f4fedf0b13cec444586155673e1769c54a50ed774ee3f

Observation dc03e466-d999-4f92-9c61-9f138d149bce · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-05T05:52:53.239946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T05:52:52.946223Z digest=sha256:747b5a0f86fc7316bee18bdc8ce9a1c0bf9832c003c7ffc604023784ec843928

Observation a9dfda0c-05de-44b3-a9d7-1e3fee5c50c8 · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-05T05:52:53.227664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T05:52:52.949812Z digest=sha256:eb430183a7c1b4591562713d55d3bab470f119298698a66c02f7295506c6d9dd

Observation 89af1587-9e02-4471-983e-404f07325b42 · outbound

This paper cites & Yuan, S.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework & Yuan, S

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:52:53.215027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T05:52:52.953346Z digest=sha256:d87a8b8ae76185e92eeab8422ed07b3a3873678eac55ccef410047bb513cce24

Observation dba88151-9d14-446d-a0be-4432f0265c22 · outbound

This paper cites P., Burke, K.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework P., Burke, K

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-05T05:52:52.956787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:52:52.956787Z digest=sha256:ea932ee82802abe30fc9af2d6cbb90d489350b6eabb92b7287cd07876205d7e5

Observation d1e6db38-38e5-443c-815a-e736edae153a · outbound

This paper cites an unresolved cited work.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-05T05:52:53.194076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T05:52:52.960420Z digest=sha256:61e31f10651e345f5a2d26dad73417a7c74f12e4a0d4b7c81af10706d62e8f20

Observation 5f699cae-9e92-4a21-9a9c-707cce3e9356 · outbound

This paper cites Decoupled Weight Decay Regularization.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Decoupled Weight Decay Regularization

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-05T05:52:52.964021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:52:52.964021Z digest=sha256:55585eb6f81a6d2a90a0e045c70422c0b02e0f95a819e241cbf2e185e9a46d50

Observation beca0e3b-e59f-4db6-a901-74a653dafff2 · outbound

This paper cites On the Convergence of Adam and Beyond.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework On the Convergence of Adam and Beyond

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-05T05:52:52.967806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:52:52.967806Z digest=sha256:f4712825b9f09b585f0504e59aba204f7cd74b48201afbe2d1068db7d349f8b8

Pith citing papers

No inbound Pith citation observations are available.