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  1. Home
  2. Signal Canvas
  3. Shape Representation using Gaussian Process mixture models
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Shape Representation using Gaussian Process mixture models

Fresh3d ago
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0.0/10

Compared to this week’s papers

Evidence fresh

Evidence Receipt

Freshness: 2026-04-02T20:55:45.114352+00:00

Claims: 0

References: 48

Proof: unverified

Freshness: fresh

Source paper: Shape Representation using Gaussian Process mixture models

PDF: https://arxiv.org/pdf/2604.00862v1

Source count: 3

Coverage: 50%

Last proof check: 2026-04-02T21:01:48.782Z

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Shape Representation using Gaussian Process mixture models

Overall score: 5/10
Lineage: a44b7b3102b9…
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Canonical Paper Receipt

Last verification: 2026-04-02T21:01:48.782Z

Freshness: fresh

Proof: unverified

Repo: missing

References: 48

Sources: 3

Coverage: 50%

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Unknowns
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Dimensions overall score 5.0

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Builds On This
GGMPs: Generalized Gaussian Mixture Processes
Score 4.0down
Builds On This
GaussianGPT: Towards Autoregressive 3D Gaussian Scene Generation
Score 4.0down
Prior Work
Simplex-to-Euclidean Bijection for Conjugate and Calibrated Multiclass Gaussian Process
Score 5.0stable
Prior Work
From Basis to Basis: Gaussian Particle Representation for Interpretable PDE Operators
Score 5.0stable
Higher Viability
GS^2: Graph-based Spatial Distribution Optimization for Compact 3D Gaussian Splatting
Score 7.0up
Higher Viability
Director: Instance-aware Gaussian Splatting for Dynamic Scene Modeling and Understanding
Score 7.0up
Higher Viability
Confidence-Based Mesh Extraction from 3D Gaussians
Score 7.0up
Higher Viability
3D Scene Rendering with Multimodal Gaussian Splatting
Score 6.0up

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