MatrixNet: Learning over symmetry groups using learned group representations | Paper Citation Record

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This paper cites Attention is all you need.

MatrixNet: Learning over symmetry groups using learned group representations Attention is all you need

Reference 1

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This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

MatrixNet: Learning over symmetry groups using learned group representations An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 2

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

MatrixNet: Learning over symmetry groups using learned group representations Semi-Supervised Classification with Graph Convolutional Networks

Reference 3

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This paper cites Spectral Networks and Locally Connected Networks on Graphs.

MatrixNet: Learning over symmetry groups using learned group representations Spectral Networks and Locally Connected Networks on Graphs

Reference 4

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This paper cites $\mathrm{SO}(2)$-Equivariant Reinforcement Learning.

MatrixNet: Learning over symmetry groups using learned group representations $\mathrm{SO}(2)$-Equivariant Reinforcement Learning

Reference 5

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This paper cites Solving the rubik’s cube with deep reinforcement learning and search.

MatrixNet: Learning over symmetry groups using learned group representations Solving the rubik’s cube with deep reinforcement learning and search

Reference 6

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This paper cites Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold.

MatrixNet: Learning over symmetry groups using learned group representations Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold

Reference 7

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This paper cites Sampling using su (n) gauge equivariant flows.

MatrixNet: Learning over symmetry groups using learned group representations Sampling using su (n) gauge equivariant flows

Reference 8

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This paper cites Fourier theoretic probabilistic inference over permutations.

MatrixNet: Learning over symmetry groups using learned group representations Fourier theoretic probabilistic inference over permutations

Reference 9

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Observation 82a3d6f2-e18d-49d6-aef1-7904aa02d0c5 · outbound

This paper cites Explorations in Homeomorphic Variational Auto-Encoding.

MatrixNet: Learning over symmetry groups using learned group representations Explorations in Homeomorphic Variational Auto-Encoding

Reference 10

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This paper cites On the continuity of rotation represen- tations in neural networks.

MatrixNet: Learning over symmetry groups using learned group representations On the continuity of rotation represen- tations in neural networks

Reference 11

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This paper cites Deep regression on manifolds: a 3d rotation case study.

MatrixNet: Learning over symmetry groups using learned group representations Deep regression on manifolds: a 3d rotation case study

Reference 12

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Observation 14fe6fe9-c552-4a5d-9fd0-44143866119a · outbound

This paper cites Learning with 3D rotations, a hitchhiker's guide to SO(3).

MatrixNet: Learning over symmetry groups using learned group representations Learning with 3D rotations, a hitchhiker's guide to SO(3)

Reference 13

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This paper cites Checkelsky, and Tess Smidt.

MatrixNet: Learning over symmetry groups using learned group representations Checkelsky, and Tess Smidt

Reference 14

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This paper cites Differentiable mathematical programming for object- centric representation learning.

MatrixNet: Learning over symmetry groups using learned group representations Differentiable mathematical programming for object- centric representation learning

Reference 15

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This paper cites Mechanistic neural networks for scientific machine learning.

MatrixNet: Learning over symmetry groups using learned group representations Mechanistic neural networks for scientific machine learning

Reference 16

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This paper cites Bronstein, Joan Bruna, Taco Cohen, and Petar Veliˇckovi´c.

MatrixNet: Learning over symmetry groups using learned group representations Bronstein, Joan Bruna, Taco Cohen, and Petar Veliˇckovi´c

Reference 17

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This paper cites Group equivariant convolutional networks.

MatrixNet: Learning over symmetry groups using learned group representations Group equivariant convolutional networks

Reference 18

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This paper cites On the generalization of equivariance and convolution in neural networks to the action of compact groups.

MatrixNet: Learning over symmetry groups using learned group representations On the generalization of equivariance and convolution in neural networks to the action of compact groups

Reference 19

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

MatrixNet: Learning over symmetry groups using learned group representations Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

Reference 20

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This paper cites Equivariant adaptation of large pretrained models.

MatrixNet: Learning over symmetry groups using learned group representations Equivariant adaptation of large pretrained models

Reference 21

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This paper cites Learning local equivariant representations for large-scale atomistic dynamics.

MatrixNet: Learning over symmetry groups using learned group representations Learning local equivariant representations for large-scale atomistic dynamics

Reference 22

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This paper cites Numerical calabi-yau metrics from holomorphic networks.

MatrixNet: Learning over symmetry groups using learned group representations Numerical calabi-yau metrics from holomorphic networks

Reference 23

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This paper cites Equivariant descriptor fields: Se(3)- equivariant energy-based models for end-to-end visual robotic manipulation learning, 2023.

MatrixNet: Learning over symmetry groups using learned group representations Equivariant descriptor fields: Se(3)- equivariant energy-based models for end-to-end visual robotic manipulation learning, 2023

Reference 24

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This paper cites Contrastive learning of structured world models.

MatrixNet: Learning over symmetry groups using learned group representations Contrastive learning of structured world models

Reference 25

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This paper cites Self-supervised learning of split invariant equivariant representations.

MatrixNet: Learning over symmetry groups using learned group representations Self-supervised learning of split invariant equivariant representations

Reference 26

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This paper cites Equivariant self-supervised learning: Encouraging equivariance in represen- tations.

MatrixNet: Learning over symmetry groups using learned group representations Equivariant self-supervised learning: Encouraging equivariance in represen- tations

Reference 27

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This paper cites Learning disentangled representations and group structure of dynamical environments.

MatrixNet: Learning over symmetry groups using learned group representations Learning disentangled representations and group structure of dynamical environments

Reference 28

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This paper cites Learning symmetric embeddings for equivariant world models.

MatrixNet: Learning over symmetry groups using learned group representations Learning symmetric embeddings for equivariant world models

Reference 29

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This paper cites Automatic symmetry discovery with lie algebra convolutional network.

MatrixNet: Learning over symmetry groups using learned group representations Automatic symmetry discovery with lie algebra convolutional network

Reference 30

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MatrixNet: Learning over symmetry groups using learned group representations Unresolved cited work

Reference 31

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This paper cites Latent space symmetry discovery.

MatrixNet: Learning over symmetry groups using learned group representations Latent space symmetry discovery

Reference 32

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This paper cites Algebraically-informed deep networks (aidn): A deep learning approach to represent algebraic structures, 2021.

MatrixNet: Learning over symmetry groups using learned group representations Algebraically-informed deep networks (aidn): A deep learning approach to represent algebraic structures, 2021

Reference 33

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MatrixNet: Learning over symmetry groups using learned group representations Mathprompter: Mathematical reasoning using large language models, 2023

Reference 34

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This paper cites Trinh, Yuhuai Wu, Quoc V.

MatrixNet: Learning over symmetry groups using learned group representations Trinh, Yuhuai Wu, Quoc V

Reference 35

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This paper cites Physics informed deep learning (part i): Data-driven solutions of nonlinear partial differential equations, 2017.

MatrixNet: Learning over symmetry groups using learned group representations Physics informed deep learning (part i): Data-driven solutions of nonlinear partial differential equations, 2017

Reference 36

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This paper cites ForecastNet: A Time-Variant Deep Feed- Forward Neural Network Architecture for Multi-step-Ahead Time-Series Forecasting , page 579–591.

MatrixNet: Learning over symmetry groups using learned group representations ForecastNet: A Time-Variant Deep Feed- Forward Neural Network Architecture for Multi-step-Ahead Time-Series Forecasting , page 579–591

Reference 37

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MatrixNet: Learning over symmetry groups using learned group representations Fourcastnet: A global data-driven high-resolution weather model using adaptive fourier neural operators, 2022

Reference 38

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This paper cites Advancing mathematics by guiding human intuition with ai.

MatrixNet: Learning over symmetry groups using learned group representations Advancing mathematics by guiding human intuition with ai

Reference 39

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MatrixNet: Learning over symmetry groups using learned group representations Unresolved cited work

Reference 40

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This paper cites Ueber den arithmetischen charakter der coefficienten der substitutionen endlicher linearer substitutionsgruppen.

MatrixNet: Learning over symmetry groups using learned group representations Ueber den arithmetischen charakter der coefficienten der substitutionen endlicher linearer substitutionsgruppen

Reference 41

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This paper cites Introduction to representations of braid groups.

MatrixNet: Learning over symmetry groups using learned group representations Introduction to representations of braid groups

Reference 42

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This paper cites Representation theory: a first course, volume 129.

MatrixNet: Learning over symmetry groups using learned group representations Representation theory: a first course, volume 129

Reference 43

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This paper cites A Thurston compactification of the space of stability conditions.

MatrixNet: Learning over symmetry groups using learned group representations A Thurston compactification of the space of stability conditions

Reference 44

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MatrixNet: Learning over symmetry groups using learned group representations Braid group actions on derived categories of coherent sheaves

Reference 45

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MatrixNet: Learning over symmetry groups using learned group representations Picard groups for derived module categories

Reference 46

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MatrixNet: Learning over symmetry groups using learned group representations Unresolved cited work

Reference 47

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This paper cites Quivers, Floer cohomology, and braid group actions.

MatrixNet: Learning over symmetry groups using learned group representations Quivers, Floer cohomology, and braid group actions

Reference 48

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MatrixNet: Learning over symmetry groups using learned group representations Humphreys

Reference 49

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This paper cites Smith, Mateusz Paprocki, Ondˇrej ˇCertík, Sergey B.

MatrixNet: Learning over symmetry groups using learned group representations Smith, Mateusz Paprocki, Ondˇrej ˇCertík, Sergey B

Reference 50

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MatrixNet: Learning over symmetry groups using learned group representations Unresolved cited work

Reference 51

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This paper cites That is, record the number of occurrences of Pi[d] separately for every possible d.

MatrixNet: Learning over symmetry groups using learned group representations That is, record the number of occurrences of Pi[d] separately for every possible d

Reference 52

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This paper cites This constraint can be explicitly described for any Bn via a geometric model (due to Khovanov–Seidel [48]) for objects in the category Cn.

MatrixNet: Learning over symmetry groups using learned group representations This constraint can be explicitly described for any Bn via a geometric model (due to Khovanov–Seidel [48]) for objects in the category Cn

Reference 53

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MatrixNet: Learning over symmetry groups using learned group representations Unresolved cited work

Reference 54

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This paper cites All of the questions above remain open for all but the simplest cases of Artin–Tits groups.

MatrixNet: Learning over symmetry groups using learned group representations All of the questions above remain open for all but the simplest cases of Artin–Tits groups

Reference 55

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