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Paper Citation Record · LEDGER

Sobek: Streaming Equivariant Tensor Product Convolutions

As of 8 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2607.18074.

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

pith.paper-citation-record.v1
2607.18074 v1

Coverage vector

measured 22 of 22 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-01T16:22:27.643590Z

measured 22 of 22 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

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22 of 22 outbound references displayed

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Outbound references

Observation e3774c19-9a6f-4828-8a1c-4de42c0d6bbf · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

Sobek: Streaming Equivariant Tensor Product Convolutions Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 1

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Observation 1983f66a-0956-49f7-9036-98586a3efbc6 · outbound

This paper cites Clebsch–gordan nets: A fully fourier space spherical convolutional neural network.

Sobek: Streaming Equivariant Tensor Product Convolutions Clebsch–gordan nets: A fully fourier space spherical convolutional neural network

Reference 2

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Observation 88eb5461-eaa9-4b7d-9d30-4f337f408c9f · outbound

This paper cites Fuchs, Daniel E.

Sobek: Streaming Equivariant Tensor Product Convolutions Fuchs, Daniel E

Reference 3

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Observation 84f292f0-542e-46da-82bd-7c2b9fd4350d · outbound

This paper cites Bekkers, and Max Welling.

Sobek: Streaming Equivariant Tensor Product Convolutions Bekkers, and Max Welling

Reference 4

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source=pdf_text observed=2026-08-01T16:22:26.672329Z digest=sha256:d5cee6e2296d54af68363bc7f0e0b11ad6251a992753718b79e9972110d34c8e

Observation a236224d-9c85-4739-93d6-b166609a4c21 · outbound

This paper cites Tensor field networks: Rotation- and translation-equivariant neural networks for 3d point clouds, 2018.

Sobek: Streaming Equivariant Tensor Product Convolutions Tensor field networks: Rotation- and translation-equivariant neural networks for 3d point clouds, 2018

Reference 5

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Observation a2a0a2c3-0391-497c-a6aa-d8f02a2f74a0 · outbound

This paper cites Mailoa, Mordechai Kornbluth, Nicola Molinari, Tess E.

Sobek: Streaming Equivariant Tensor Product Convolutions Mailoa, Mordechai Kornbluth, Nicola Molinari, Tess E

Reference 6

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Observation 0625eb34-b343-446d-aa57-209a54e3ca73 · outbound

This paper cites Kovács, Gregor N.

Sobek: Streaming Equivariant Tensor Product Convolutions Kovács, Gregor N

Reference 7

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Observation c3e9fe40-6d5b-47a5-9c68-086d6d2ecb3f · outbound

This paper cites Equiformer: Equivariant graph attention transformer for 3d atomistic graphs.

Sobek: Streaming Equivariant Tensor Product Convolutions Equiformer: Equivariant graph attention transformer for 3d atomistic graphs

Reference 8

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source=pdf_text observed=2026-08-01T16:22:27.191190Z digest=sha256:7d33b52d41567955ed8ff37b07ab962c166f8ac15b6a2500033676e83261fe2c

Observation ab8d0717-bba6-4630-896e-9ab26c58a9c6 · outbound

This paper cites Owen, Mordechai Kornbluth, and Boris Kozinsky.

Sobek: Streaming Equivariant Tensor Product Convolutions Owen, Mordechai Kornbluth, and Boris Kozinsky

Reference 9

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Observation 2058cb89-577b-40c0-91dc-65b70f9ecf88 · outbound

This paper cites The price of freedom: Exploring expressivity and runtime tradeoffs in equivariant tensor products.

Sobek: Streaming Equivariant Tensor Product Convolutions The price of freedom: Exploring expressivity and runtime tradeoffs in equivariant tensor products

Reference 10

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source=pdf_text observed=2026-08-01T16:22:27.354294Z digest=sha256:84b4163b44538f55ace06a32f95457b2f5467c5b4a9d8bc7f59aacda7d9ddff0

Observation b94ebab8-fa52-4cc2-923c-313411a18fc3 · outbound

This paper cites An efficient sparse kernel generator for O(3)-equivariant deep networks.

Sobek: Streaming Equivariant Tensor Product Convolutions An efficient sparse kernel generator for O(3)-equivariant deep networks

Reference 11

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source=pdf_text observed=2026-08-01T16:22:27.436889Z digest=sha256:0b223e0e4e8ed173acd523a75c2f33a25bc5c4c71177b1d08a8ea3610c54d583

Observation 6c4b1452-3692-46b4-a162-524868e9dbb9 · outbound

This paper cites cuEquivariance.

Sobek: Streaming Equivariant Tensor Product Convolutions cuEquivariance

Reference 12

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Observation e342eb3d-3d27-41ae-8447-bcff0719197d · outbound

This paper cites Wood, Abhishek Das, and Tess Smidt.

Sobek: Streaming Equivariant Tensor Product Convolutions Wood, Abhishek Das, and Tess Smidt

Reference 13

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Observation b514ebc0-e6aa-40ec-b31f-c5c73e59ae34 · outbound

This paper cites e3nn: Euclidean Neural Networks.

Sobek: Streaming Equivariant Tensor Product Convolutions e3nn: Euclidean Neural Networks

Reference 14

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Observation 9ee6991e-5ce7-4793-a12f-3c18eec5b7bd · outbound

This paper cites Tensor product.

Sobek: Streaming Equivariant Tensor Product Convolutions Tensor product

Reference 15

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Observation 31f946d2-6d8f-44fb-b77d-c72b15b2aae0 · outbound

This paper cites Kernel operations on the GPU, with autodiff, without memory overflows.Journal of Machine Learning Research, 22(74):1–6, 2021.

Sobek: Streaming Equivariant Tensor Product Convolutions Kernel operations on the GPU, with autodiff, without memory overflows.Journal of Machine Learning Research, 22(74):1–6, 2021

Reference 16

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Observation 30209936-ed35-4023-9fe2-a55ccf7d6728 · outbound

This paper cites Fu, Stefano Ermon, Atri Rudra, and Christopher Ré.

Sobek: Streaming Equivariant Tensor Product Convolutions Fu, Stefano Ermon, Atri Rudra, and Christopher Ré

Reference 17

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Observation 202a452b-85de-4f2e-a9c8-1df7e15e8e81 · outbound

This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

Sobek: Streaming Equivariant Tensor Product Convolutions FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 18

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Observation 10295f4d-dd6e-411b-b61d-723b529d0fbf · outbound

This paper cites Speeding up MACE: Low-precision tricks for equivarient force fields, 2025.

Sobek: Streaming Equivariant Tensor Product Convolutions Speeding up MACE: Low-precision tricks for equivarient force fields, 2025

Reference 19

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Observation bb3263be-3258-4208-a9b6-b2e0f6cf62a3 · outbound

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Sobek: Streaming Equivariant Tensor Product Convolutions Unresolved cited work

Reference 20

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Observation 102205ca-4329-40e5-96ff-4d24c394cc64 · outbound

This paper cites Lawrence Zitnick.

Sobek: Streaming Equivariant Tensor Product Convolutions Lawrence Zitnick

Reference 21

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Observation d6ff9443-d06f-4d11-862d-c97bfedc3166 · outbound

This paper cites Equivariant neural operator learning with graphon convolution.

Sobek: Streaming Equivariant Tensor Product Convolutions Equivariant neural operator learning with graphon convolution

Reference 22

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