Paper Citation Record · LEDGER

E3x: $\mathrm{E}(3)$-Equivariant Deep Learning Made Easy

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2401.07595.

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

pith.paper-citation-record.v1
2401.07595 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:09:26.207377Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T16:54:16.405166Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 25425301-90d1-42f6-97a7-f944a8e56677 · inbound

An Efficient Sparse Kernel Generator for O(3)-Equivariant Deep Networks cites this paper.

An Efficient Sparse Kernel Generator for O(3)-Equivariant Deep Networks E3x: $\mathrm{E}(3)$-Equivariant Deep Learning Made Easy

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T15:59:39.065839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b00ad6e3-adfe-444e-834c-aff602c73eaa · inbound

Machine Learning Interatomic Potentials: library for efficient training, model development and simulation of molecular systems cites this paper.

Machine Learning Interatomic Potentials: library for efficient training, model development and simulation of molecular systems E3x: $\mathrm{E}(3)$-Equivariant Deep Learning Made Easy

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T13:13:23.210607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ca94b6d-0d16-4a84-9e1e-e4fbde63432a · inbound

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products cites this paper.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products E3x: $\mathrm{E}(3)$-Equivariant Deep Learning Made Easy

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T20:09:26.207377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0728b531-c0a8-4e38-a10e-1fc175df9d4d · inbound

Simultaneous Learning of Static and Dynamic Charges cites this paper.

Simultaneous Learning of Static and Dynamic Charges E3x: $\mathrm{E}(3)$-Equivariant Deep Learning Made Easy

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-21T16:54:16.407704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 49b1681f-bc9a-414b-a69b-7bccd0e1b442 · inbound

Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks cites this paper.

Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks E3x: $\mathrm{E}(3)$-Equivariant Deep Learning Made Easy

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-15T03:09:43.992794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6ff016c5-aaec-45d4-b813-024692f0335c · inbound

Edge Cluster Expansion with Radial Rotary Attention for Interatomic Potentials cites this paper.

Edge Cluster Expansion with Radial Rotary Attention for Interatomic Potentials E3x: $\mathrm{E}(3)$-Equivariant Deep Learning Made Easy

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-14T10:08:16.536665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.