Paper Citation Record · LEDGER

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products

As of 19 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2506.13523.

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

pith.paper-citation-record.v1
2506.13523 v2

Coverage vector

measured 50 of 50 reference resolution

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measured 51 of 51 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

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External citation measurements

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Outbound references

Observation f8505641-5256-40c1-ada6-7d39b9e0f6fc · outbound

This paper cites write newline.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products write newline

Reference 1

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This paper cites and Xia, T.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products and Xia, T

Reference 2

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This paper cites and Isard, M.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products and Isard, M

Reference 3

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This paper cites P., Simm, G.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products P., Simm, G

Reference 4

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This paper cites P., Kornbluth, M., Molinari, N., Smidt, T.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products P., Kornbluth, M., Molinari, N., Smidt, T

Reference 5

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Unresolved cited work

Reference 6

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

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products An Efficient Sparse Kernel Generator for O(3)-Equivariant Deep Networks

Reference 7

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This paper cites J., Leary, C., Maclaurin, D., Necula, G., Paszke, A., Vander P las, J., Wanderman- M ilne, S., and Zhang, Q.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products J., Leary, C., Maclaurin, D., Necula, G., Paszke, A., Vander P las, J., Wanderman- M ilne, S., and Zhang, Q

Reference 8

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This paper cites Does equivariance matter at scale?.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Does equivariance matter at scale?

Reference 9

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This paper cites Are high-degree representations really unnecessary in equivariant graph neural networks? In The Thirty-eighth Annual Conference on Neural Information Processing Systems.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Are high-degree representations really unnecessary in equivariant graph neural networks? In The Thirty-eighth Annual Conference on Neural Information Processing Systems

Reference 10

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This paper cites On the role of gradients for machine learning of molecular energies and forces.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products On the role of gradients for machine learning of molecular energies and forces

Reference 11

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This paper cites G., Mavor-Parker, A.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products G., Mavor-Parker, A

Reference 12

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This paper cites S., Dresselhaus, G., and Jorio, A.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products S., Dresselhaus, G., and Jorio, A

Reference 13

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This paper cites Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE

Reference 14

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This paper cites T., and Muller, K.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products T., and Muller, K

Reference 15

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products C., Soklaski, R., Axelrod, S., Samsi, S., Gómez-Bombarelli, R., Coley, C

Reference 16

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This paper cites A recipe for charge density prediction, 2024.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products A recipe for charge density prediction, 2024

Reference 17

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Unresolved cited work

Reference 18

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products e3nn: Euclidean Neural Networks

Reference 19

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products M., Rockmore, D

Reference 20

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products G., Vignac, C., and Welling, M

Reference 21

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Unresolved cited work

Reference 22

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This paper cites N-body Networks: a Covariant Hierarchical Neural Network Architecture for Learning Atomic Potentials.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products N-body Networks: a Covariant Hierarchical Neural Network Architecture for Learning Atomic Potentials

Reference 23

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Clebsch-gordan nets: a fully fourier space spherical convolutional neural network

Reference 24

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products P., Oord, C

Reference 25

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Fourcastnet: Accelerating global high-resolution weather forecasting using adaptive fourier neural operators

Reference 26

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products H., Yadollahpour, P., Watkins, A., Frey, N

Reference 28

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products and Smidt, T

Reference 29

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products

Reference 30

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Complete and Efficient Covariants for 3D Point Configurations with Application to Learning Molecular Quantum Properties

Reference 31

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products J., Kornbluth, M., and Kozinsky, B

Reference 33

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products cuequivariance, 2024

Reference 34

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products J., Torrisi, S

Reference 35

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products and Zitnick, C

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products A., Tecot, L., Geiger, M., and Smidt, T

Reference 37

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Xla : Compiling machine learning for peak performance, 2020

Reference 38

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products High-Rank Irreducible Cartesian Tensor Decomposition and Bases of Equivariant Spaces

Reference 39

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Operator Fusion in XLA: Analysis and Evaluation

Reference 40

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products High-performance training and inference for deep equivariant interatomic potentials

Reference 41

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Why the compute throughputs value is different from the actual performance (peak performance)?, 2023

Reference 42

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

Reference 43

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

Reference 44

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products A., Moskalev, A

Reference 45

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products 3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data

Reference 46

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Fast and accurate spherical harmonics products

Reference 47

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Hierarchical Roofline Analysis: How to Collect Data using Performance Tools on Intel CPUs and NVIDIA GPUs

Reference 48

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Hierarchical Roofline Performance Analysis for Deep Learning Applications

Reference 49

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The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Higher-rank irreducible cartesian tensors for equivariant message passing

Reference 50

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Pith citing papers

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Reconstructing local environments from concise atomistic representations cites this paper.

Reconstructing local environments from concise atomistic representations The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products

Reference 64

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