Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T05:52:52.967806Z
Paper Citation Record · LEDGER
As of 8 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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T05:52:52.967806Z
One-hop event checks from named stored sources.
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
A source-named dated measurement, never combined with another source.
Source: cited_works
49 of 49 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation ceeef588-f122-488c-aec5-c32e752791a3 · outbound
Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
Reference 1
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework T., Gastegger, M., Tkatchenko, A., Müller, K.-R
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
Reference 10
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
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Observation 874f3723-9e47-47c0-bff9-53032231ba41 · outbound
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
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Observation 1880a535-3347-4caa-8d1e-688524cabe1d · outbound
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
Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Relational inductive biases, deep learning, and graph networks
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Observation 95374d4e-1702-450a-9fa3-8574b6e1188a · outbound
Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Semi-Supervised Classification with Graph Convolutional Networks
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Graph Neural Networks: A Review of Methods and Applications
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework F., Vinyals, O
Reference 19
Source-reported events for the cited work
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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
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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
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Observation 17bf52f7-ee73-4c97-ae20-36c9da78fbbc · outbound
Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
Reference 22
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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
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework & Furthmüller, J
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework & Furthmüller, J
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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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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
Reference 30
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics
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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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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
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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
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
Reference 38
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework & Koshino, M
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
Reference 40
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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
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Reference 42
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
Reference 43
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
Reference 44
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
Reference 46
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Reference 47
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework P., Burke, K
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Unresolved cited work
Reference 49
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework Decoupled Weight Decay Regularization
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Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework On the Convergence of Adam and Beyond
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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