On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting | Paper Citation Record

Observation 1c5dd389-5018-40df-9dc6-02015e36ab49 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Nerf: Representing scenes as neural radiance fields for view synthesis,

Reference 1

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Observation db452fd8-cf83-4f8e-8a8c-69250022d87a · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting 3d gaussian splatting for real-time radiance field rendering,

Reference 2

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Observation d226da13-0b2e-4f26-a130-806ffa71bd2e · outbound

This paper cites 4d gaussian splatting for real-time dynamic scene rendering,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting 4d gaussian splatting for real-time dynamic scene rendering,

Reference 3

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Observation b3460248-7f9d-4ecd-bb6f-c8b71f4d4848 · outbound

This paper cites Spacetime gaussian feature splatting for real-time dynamic view synthesis,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Spacetime gaussian feature splatting for real-time dynamic view synthesis,

Reference 4

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Observation 47a8010d-b58e-4eae-bb70-b579edb446eb · outbound

This paper cites Per-gaussian embedding-based deformation for deformable 3d gaussian splatting,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Per-gaussian embedding-based deformation for deformable 3d gaussian splatting,

Reference 5

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Observation 0b6ab19a-c1c4-4c90-9c3e-51c84dcb0bc4 · outbound

This paper cites Fully explicit dynamic gaussian splatting,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Fully explicit dynamic gaussian splatting,

Reference 6

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Observation 4cc4172b-1454-419a-920f-eba00891e15c · outbound

This paper cites Grid4d: 4d decomposed hash encoding for high-fidelity dynamic gaussian splatting,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Grid4d: 4d decomposed hash encoding for high-fidelity dynamic gaussian splatting,

Reference 7

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Observation 6ff2743e-49b4-430f-80d3-da18b05d200d · outbound

This paper cites The plenoptic function and the elements of early vision,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting The plenoptic function and the elements of early vision,

Reference 8

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Observation 35ee57c4-94c4-4d6c-9a0f-e60dcf41bb9b · outbound

This paper cites Light field rendering,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Light field rendering,

Reference 9

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Observation 813e4371-5638-4f3b-9662-ea58f20d662f · outbound

This paper cites Ms-nerf: Multi- space neural radiance fields,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Ms-nerf: Multi- space neural radiance fields,

Reference 10

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Observation 7c02e419-1b62-4d12-afcf-682ef77d9f82 · outbound

This paper cites Ref-nerf: Structured view-dependent appearance for neural radiance fields,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Ref-nerf: Structured view-dependent appearance for neural radiance fields,

Reference 11

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Observation abeb9f6a-333f-47b4-aaf8-cf1bd1b15cab · outbound

This paper cites Forward flow for novel view synthesis of dynamic scenes,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Forward flow for novel view synthesis of dynamic scenes,

Reference 12

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Observation 39f3a0b6-53d9-4db9-ba4a-682683487151 · outbound

This paper cites Devrf: Fast deformable voxel radiance fields for dynamic scenes,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Devrf: Fast deformable voxel radiance fields for dynamic scenes,

Reference 13

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Observation 014f3eda-c603-46f6-bdd6-332654b16526 · outbound

This paper cites Hypernerf: A higher-dimensional representation for topologically varying neural radiance fields,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Hypernerf: A higher-dimensional representation for topologically varying neural radiance fields,

Reference 14

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Observation 029e7544-3305-4ab3-9724-2cac4cad92b4 · outbound

This paper cites D- nerf: Neural radiance fields for dynamic scenes,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting D- nerf: Neural radiance fields for dynamic scenes,

Reference 15

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Observation 0917da17-d115-4b2d-8033-b43bf9e89234 · outbound

This paper cites Nerfplayer: A streamable dynamic scene representation with decomposed neural radiance fields,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Nerfplayer: A streamable dynamic scene representation with decomposed neural radiance fields,

Reference 16

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Observation 0d1a6e2d-44b9-469b-810c-cc685f3781bf · outbound

This paper cites Neural Trajectory Fields for Dynamic Novel View Synthesis.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Neural Trajectory Fields for Dynamic Novel View Synthesis

Reference 17

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Observation 57f3164d-5443-4979-9a9e-71a92cbd9509 · outbound

This paper cites Nerfies: Deformable neural radiance fields,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Nerfies: Deformable neural radiance fields,

Reference 18

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Observation fbcf98c4-001e-4f71-ab07-c03c24ceb1a3 · outbound

This paper cites Deformgs: Scene flow in highly deformable scenes for deformable object manipulation,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Deformgs: Scene flow in highly deformable scenes for deformable object manipulation,

Reference 19

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Observation 7de9cad3-10cd-4b51-b908-c85372c171f0 · outbound

This paper cites Hexplane: A fast representation for dynamic scenes,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Hexplane: A fast representation for dynamic scenes,

Reference 20

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Observation 50d16074-c540-4785-854c-15da1badc1e0 · outbound

This paper cites K-planes: Explicit radiance fields in space, time, and appearance,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting K-planes: Explicit radiance fields in space, time, and appearance,

Reference 21

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Observation a389a2d3-3fef-4b29-ac16-f463ac911666 · outbound

This paper cites High-fidelity and real-time novel view synthesis for dynamic scenes,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting High-fidelity and real-time novel view synthesis for dynamic scenes,

Reference 22

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Observation c6a0cf2b-051a-45c6-ba8b-db8077df3f4c · outbound

This paper cites Tensor4d: Efficient neural 4d decomposition for high-fidelity dynamic reconstruction and rendering,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Tensor4d: Efficient neural 4d decomposition for high-fidelity dynamic reconstruction and rendering,

Reference 23

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Observation 05aa97ac-81f0-40dc-b6e0-3c1af7a72d5d · outbound

This paper cites Masked space-time hash encoding for efficient dynamic scene reconstruction,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Masked space-time hash encoding for efficient dynamic scene reconstruction,

Reference 24

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Observation 63ce5813-a12c-4dc4-8b5d-2a429bf054f0 · outbound

This paper cites Neural residual radiance fields for streamably free-viewpoint videos,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Neural residual radiance fields for streamably free-viewpoint videos,

Reference 25

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Observation 4da73e63-a012-4f51-966f-d86861aa9ccb · outbound

This paper cites Hac++: Towards 100x compression of 3d gaussian splatting,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Hac++: Towards 100x compression of 3d gaussian splatting,

Reference 26

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Observation a022574d-66d2-442f-8726-7e671fb1fb6c · outbound

This paper cites Z-splat: Z-axis gaussian splatting for camera-sonar fusion,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Z-splat: Z-axis gaussian splatting for camera-sonar fusion,

Reference 27

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Observation 2cbaf77e-f7b9-43dd-8965-21a8f448a5f1 · outbound

This paper cites 3dgstream: On- the-fly training of 3d gaussians for efficient streaming of photo-realistic free-viewpoint videos,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting 3dgstream: On- the-fly training of 3d gaussians for efficient streaming of photo-realistic free-viewpoint videos,

Reference 28

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Observation 2bae921e-9cf1-4822-85cd-99d3ca7cee0d · outbound

This paper cites Dynamics-aware gaussian splatting streaming towards fast on-the-fly 4d reconstruction,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Dynamics-aware gaussian splatting streaming towards fast on-the-fly 4d reconstruction,

Reference 29

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Observation d6101381-1ec0-44e3-b6d2-71ca036202fe · outbound

This paper cites 4d gaussian splatting with scale- aware residual field and adaptive optimization for real-time rendering of temporally complex dynamic scenes,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting 4d gaussian splatting with scale- aware residual field and adaptive optimization for real-time rendering of temporally complex dynamic scenes,

Reference 30

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Observation 090eb632-46b5-4e3b-9e59-b571c79f229d · outbound

This paper cites SwinGS: Sliding Window Gaussian Splatting for Volumetric Video Streaming with Arbitrary Length.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting SwinGS: Sliding Window Gaussian Splatting for Volumetric Video Streaming with Arbitrary Length

Reference 31

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Observation b7ca7380-088b-4ae0-8d95-eed1f766bfe3 · outbound

This paper cites 4d-rotor gaussian splatting: towards efficient novel view synthesis for dynamic scenes,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting 4d-rotor gaussian splatting: towards efficient novel view synthesis for dynamic scenes,

Reference 32

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Observation b8182471-c43e-4e7c-9e9b-506d7c18573c · outbound

This paper cites Gaussian-flow: 4d reconstruction with dynamic 3d gaussian particle,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Gaussian-flow: 4d reconstruction with dynamic 3d gaussian particle,

Reference 33

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Observation 139450e8-98a9-43d0-b7ca-c37d315b621a · outbound

This paper cites Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis,

Reference 34

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Observation 6a1efa17-70cf-41a7-8b7f-f3f095403793 · outbound

This paper cites Deformable 3d gaussians for high-fidelity monocular dynamic scene reconstruction,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Deformable 3d gaussians for high-fidelity monocular dynamic scene reconstruction,

Reference 35

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Observation a81d7044-6ccd-4e7c-b096-c93f1bed7f49 · outbound

This paper cites Dynmf: Neural motion factorization for real-time dynamic view synthesis with 3d gaussian splatting,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Dynmf: Neural motion factorization for real-time dynamic view synthesis with 3d gaussian splatting,

Reference 36

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Observation 80b57355-62f6-4da4-94bc-7c6b35602bed · outbound

This paper cites Gaufre: Gaussian deformation fields for real-time dynamic novel view synthesis,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Gaufre: Gaussian deformation fields for real-time dynamic novel view synthesis,

Reference 37

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Observation 4bafbd5b-b3e7-4b3c-92ee-5324fa2a4ffe · outbound

This paper cites Sc-gs: Sparse-controlled gaussian splatting for editable dynamic scenes,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Sc-gs: Sparse-controlled gaussian splatting for editable dynamic scenes,

Reference 38

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Observation 9e851982-a3c3-45da-accc-75ceffaf8314 · outbound

This paper cites Cogs: Controllable gaussian splatting,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Cogs: Controllable gaussian splatting,

Reference 39

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Observation f6a589db-ac66-4fc1-a114-af10a3f9d99b · outbound

This paper cites Dash: 4d hash encoding with self-supervised decomposition for real-time dynamic scene rendering,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Dash: 4d hash encoding with self-supervised decomposition for real-time dynamic scene rendering,

Reference 40

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Observation 901e1b07-f045-4a22-a952-2176f9cb4892 · outbound

This paper cites Localdygs: Multi-view global dynamic scene modeling via adaptive local implicit feature decoupling,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Localdygs: Multi-view global dynamic scene modeling via adaptive local implicit feature decoupling,

Reference 41

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Observation 7bc664ab-6184-4ed0-9e4f-978d6d27efb0 · outbound

This paper cites Haif-gs: Hierarchical and induced flow-guided gaussian splatting for dynamic scene,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Haif-gs: Hierarchical and induced flow-guided gaussian splatting for dynamic scene,

Reference 42

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Observation 54e4881a-4552-4c62-afad-26cfee398cf5 · outbound

This paper cites Timeformer: Capturing temporal relationships of deformable 3d gaussians for robust re- construction,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Timeformer: Capturing temporal relationships of deformable 3d gaussians for robust re- construction,

Reference 43

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Observation bd5a0b8b-1861-492f-b8a5-4f0cd45f70a4 · outbound

This paper cites Freetimegs: Free gaussian primitives at anytime anywhere for dynamic scene reconstruction,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Freetimegs: Free gaussian primitives at anytime anywhere for dynamic scene reconstruction,

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Observation 07f6828c-f459-455b-bbc1-b237964e7fce · outbound

This paper cites 7dgs: Unified spatial-temporal-angular gaussian splatting,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting 7dgs: Unified spatial-temporal-angular gaussian splatting,

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Observation 8934f719-0351-405f-ba65-a9257e2cebc3 · outbound

This paper cites Modgs: Dynamic gaussian splatting from casually-captured monocular videos with depth priors,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Modgs: Dynamic gaussian splatting from casually-captured monocular videos with depth priors,

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Observation be9c6eb7-e852-4b13-af5a-6b04f1fc6a80 · outbound

This paper cites Real-time photorealistic dynamic scene representation and rendering with 4d gaussian splatting,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Real-time photorealistic dynamic scene representation and rendering with 4d gaussian splatting,

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Observation 63de6cc6-df1c-43fe-95a5-944638a0ea19 · outbound

This paper cites 4D Gaussian Splatting: Modeling Dynamic Scenes with Native 4D Primitives.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting 4D Gaussian Splatting: Modeling Dynamic Scenes with Native 4D Primitives

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Observation 9aa14a74-628b-4748-969d-90ee6d2bffa4 · outbound

This paper cites Mega: Memory-efficient 4d gaussian splatting for dynamic scenes,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Mega: Memory-efficient 4d gaussian splatting for dynamic scenes,

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Observation cf636064-c4ff-4d4b-87e9-3b86d0f68d4f · outbound

This paper cites 4d scaffold gaussian splatting with dynamic-aware anchor growing for efficient and high-fidelity dynamic scene reconstruction,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting 4d scaffold gaussian splatting with dynamic-aware anchor growing for efficient and high-fidelity dynamic scene reconstruction,

Reference 50

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Observation 7c4aef63-2a85-48b1-9ec5-ccc21660e3c4 · outbound

This paper cites Shape of motion: 4d reconstruction from a single video,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Shape of motion: 4d reconstruction from a single video,

Reference 51

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Observation dd7e1315-c080-4ca7-b0d4-1d8021c7fb1c · outbound

This paper cites Slowfast networks for video recognition,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Slowfast networks for video recognition,

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Observation defb0a22-2ed7-448b-a4eb-d8c908d62f33 · outbound

This paper cites an unresolved cited work.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Unresolved cited work

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This paper cites Animating rotation with quaternion curves,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Animating rotation with quaternion curves,

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Observation 854cb9a2-ed5e-4af5-ae96-e0a9eddabc6d · outbound

This paper cites Simple and scalable predictive uncertainty estimation using deep ensembles,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Simple and scalable predictive uncertainty estimation using deep ensembles,

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Observation c7e191a9-be1a-4441-b819-8ba0232e58c3 · outbound

This paper cites Outrageously large neural networks: The sparsely-gated mixture-of-experts layer,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Outrageously large neural networks: The sparsely-gated mixture-of-experts layer,

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Observation 082ea05f-803e-4519-a39d-7eabb0ef5b50 · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,

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Observation 6d711f72-561a-4450-9ef9-1d3f2c289205 · outbound

This paper cites Mod-squad: Designing mixtures of experts as modular multi-task learners,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Mod-squad: Designing mixtures of experts as modular multi-task learners,

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This paper cites Base layers: Simplifying training of large, sparse models,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Base layers: Simplifying training of large, sparse models,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Dselect-k: Differentiable selection in the mixture of experts with applications to multi-task learning,

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This paper cites Modeling task relationships in multi-task learning with multi-gate mixture-of-experts,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Modeling task relationships in multi-task learning with multi-gate mixture-of-experts,

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This paper cites On the representation collapse of sparse mixture of experts,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting On the representation collapse of sparse mixture of experts,

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This paper cites FastMoE: A Fast Mixture-of-Expert Training System.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting FastMoE: A Fast Mixture-of-Expert Training System

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Deepspeed-moe: Advancing mixture-of-experts inference and training to power next-generation ai scale,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Moesys: A distributed and efficient mixture-of-experts training and inference system for internet services,

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This paper cites Fastermoe: modeling and optimizing training of large-scale dynamic pre-trained models,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Fastermoe: modeling and optimizing training of large-scale dynamic pre-trained models,

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This paper cites A hybrid tensor-expert-data parallelism approach to optimize mixture-of- experts training,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting A hybrid tensor-expert-data parallelism approach to optimize mixture-of- experts training,

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This paper cites Flexmoe: Scaling large-scale sparse pre-trained model training via dynamic device placement,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Flexmoe: Scaling large-scale sparse pre-trained model training via dynamic device placement,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting {SmartMoE}: Efficiently training {Sparsely-Activated} models through combining offline and online parallelization,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Gshard: Scaling giant models with conditional computation and automatic sharding,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Uni-moe: Scaling unified multimodal llms with mixture of experts,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Moe-adapters++: Towards more efficient continual learning of vision-language models via dynamic mixture-of-experts adapters,

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This paper cites Boosting continual learning of vision-language models via mixture-of-experts adapters,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Boosting continual learning of vision-language models via mixture-of-experts adapters,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Efficient face forgery detection with mixture of experts,

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This paper cites Moead: A parameter-efficient model for multi-class anomaly detection,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Moead: A parameter-efficient model for multi-class anomaly detection,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Learning heterogeneous mixture of scene experts for large-scale neural radiance fields,

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This paper cites MoCaE: Mixture of Calibrated Experts Significantly Improves Object Detection.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting MoCaE: Mixture of Calibrated Experts Significantly Improves Object Detection

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Moe-gs: Mixture of experts for dynamic gaussian splatting,

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This paper cites 3d gaussian splatting as markov chain monte carlo,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting 3d gaussian splatting as markov chain monte carlo,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Distilling the Knowledge in a Neural Network

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This paper cites Mode: A mixture-of-experts model with mutual distillation among the experts,.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Mode: A mixture-of-experts model with mutual distillation among the experts,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Model compression, in proceedings of the 12 th acm sigkdd international conference on knowledge discovery and data mining,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Do deep nets really need to be deep?

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Neural 3d video synthesis from multi-view video,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Dataset and pipeline for multi-view light-field video,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Image quality assessment: from error visibility to structural similarity,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting The unreasonable effectiveness of deep features as a perceptual metric,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Hyperreel: High-fidelity 6-dof video with ray-conditioned sampling,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Mixed neural voxels for fast multi-view video synthesis,

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Panoptic studio: A massively multiview system for social motion capture,

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This paper cites Implementation Details This section provides implementation and training details of the proposed MoE-GS framework.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Implementation Details This section provides implementation and training details of the proposed MoE-GS framework

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Since MoE- GS reconstructs dynamic scenes by blending the outputs of multiple experts, it is critical that each expert achieves its Fig

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting This allows the router to focus solely on learning effective expert blending strategies without being influenced by the convergence rate of individual experts

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This paper cites MoE-GS effectively routes scene regions to the most suitable experts, resulting in high-fidelity reconstructions that outper- form individual models.

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting MoE-GS effectively routes scene regions to the most suitable experts, resulting in high-fidelity reconstructions that outper- form individual models

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On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting Partial expert training.Table XVIII reports the effect of partial expert training under different training budgets

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