Paper Citation Record · LEDGER

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis

As of 18 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2504.14132.

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

pith.paper-citation-record.v1
2504.14132 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:59:54.222889Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

verified exact0
verified fuzzy36
unresolved7
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ce9a5923-4229-4b3f-8d10-434d59c23af7 · outbound

This paper cites Deep learning for 3d point clouds: A survey,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Deep learning for 3d point clouds: A survey,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.927763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3dc45418-9408-43c3-9f81-b5c302cc9bce · outbound

This paper cites Deep learning for image and point cloud fusion in autonomous driving: A review,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Deep learning for image and point cloud fusion in autonomous driving: A review,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.911506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f09d33d6-259f-4916-82ab-8af6ea70912a · outbound

This paper cites A morphing-based 3D point cloud reconstruction framework for medical image processing,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis A morphing-based 3D point cloud reconstruction framework for medical image processing,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.894996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9384f9ec-a42c-45cd-85af-f279a0ce700b · outbound

This paper cites 3D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysis.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis 3D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysis

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T11:59:54.038461Z

Source-reported events for the cited work

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Observation 0324b128-891a-4b5e-9209-a7c2d0a933e1 · outbound

This paper cites Robotics dexterous grasping: The methods based on point cloud and deep learn- ing,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Robotics dexterous grasping: The methods based on point cloud and deep learn- ing,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.879197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fbdbf738-1c59-4f6f-92c1-4943ed1a5bea · outbound

This paper cites Point- Contrast: Unsupervised pre-training for 3D point cloud understanding,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Point- Contrast: Unsupervised pre-training for 3D point cloud understanding,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.863872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 98a7cd78-1a2e-437d-b26a-b17c8fe58dd6 · outbound

This paper cites CrossPoint: Self-supervised cross-modal contrastive learning for 3D point cloud understanding,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis CrossPoint: Self-supervised cross-modal contrastive learning for 3D point cloud understanding,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.847826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation df0dd6bb-66fe-4830-a15d-68f279e53fe2 · outbound

This paper cites Exploring geometry-aware contrast and clustering harmonization for self-supervised 3D object detection,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Exploring geometry-aware contrast and clustering harmonization for self-supervised 3D object detection,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.833176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d529b912-886c-4289-80cb-dfc0be70335d · outbound

This paper cites FoldingNet: Point cloud auto- encoder via deep grid deformation,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis FoldingNet: Point cloud auto- encoder via deep grid deformation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.817999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 787573be-628f-4b56-b42f-a0572d82ead1 · outbound

This paper cites Progressive seed generation auto-encoder for unsupervised point cloud learning,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Progressive seed generation auto-encoder for unsupervised point cloud learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.800825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9c4fa21d-53f6-4803-b518-c82656b85e2a · outbound

This paper cites Masked autoencoders for point cloud self-supervised learning,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Masked autoencoders for point cloud self-supervised learning,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.785287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bf2f0f3c-2192-41d0-9f3a-f49ccd22565e · outbound

This paper cites Point-M2AE: Multi-scale masked autoencoders for hierarchical point cloud pre-training,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Point-M2AE: Multi-scale masked autoencoders for hierarchical point cloud pre-training,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.770277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 85c5d594-78ca-4abc-bcab-36594a9039da · outbound

This paper cites MaskLRF: Self-supervised Pretraining via Masked Autoen- coding of Local Reference Frames for Rotation-invariant 3D Point Set Analysis,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis MaskLRF: Self-supervised Pretraining via Masked Autoen- coding of Local Reference Frames for Rotation-invariant 3D Point Set Analysis,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.755352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a679876f-6625-4236-a203-b6251c90f496 · outbound

This paper cites RI-MAE: Rotation-Invariant Masked AutoEncoders for Self-Supervised Point Cloud Representation Learning.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis RI-MAE: Rotation-Invariant Masked AutoEncoders for Self-Supervised Point Cloud Representation Learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T11:59:54.086580Z

Source-reported events for the cited work

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Observation 818515c3-cd0b-4d4f-84f8-97ca68490dde · outbound

This paper cites Masked Surfel Prediction for Self-Supervised Point Cloud Learning.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Masked Surfel Prediction for Self-Supervised Point Cloud Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T11:59:54.091857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7933d507-94cf-4179-b358-23d2d67fc113 · outbound

This paper cites Point- GPT: Auto-regressively generative pre-training from point clouds,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Point- GPT: Auto-regressively generative pre-training from point clouds,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.740557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4e95f2c4-9e01-4d35-a049-dcaa0519624c · outbound

This paper cites Enhancing Robustness to Noise Corruption for Point Cloud Recognition via Spatial Sorting and Set-Mixing Aggregation Module,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Enhancing Robustness to Noise Corruption for Point Cloud Recognition via Spatial Sorting and Set-Mixing Aggregation Module,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.725768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 32fda3c7-3010-4ff1-addb-cae58a62f9e9 · outbound

This paper cites Rotation invariant convolutions for 3D point clouds deep learning,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Rotation invariant convolutions for 3D point clouds deep learning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.710629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c7a27967-c97d-4265-b728-50955aa89a31 · outbound

This paper cites RIConv++: Effective rotation in- variant convolutions for 3D point clouds deep learning,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis RIConv++: Effective rotation in- variant convolutions for 3D point clouds deep learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.695502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 817f1d47-fb20-4d50-a89b-963529f3de73 · outbound

This paper cites Global context aware convolutions for 3D point cloud understanding,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Global context aware convolutions for 3D point cloud understanding,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.679624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5ca99645-c754-4aec-b222-220d5d7142c2 · outbound

This paper cites Rotation invariant point cloud analysis: Where local geometry meets global topology,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Rotation invariant point cloud analysis: Where local geometry meets global topology,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.665300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b3d14284-53a4-43b4-9650-2a848f818181 · outbound

This paper cites an unresolved cited work.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:59:54.649947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 91debc87-05dc-401a-a86e-f1b3b030e7be · outbound

This paper cites The devil is in the pose: Ambiguity-free 3D rotation-invariant learning via pose-aware convolution,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis The devil is in the pose: Ambiguity-free 3D rotation-invariant learning via pose-aware convolution,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.634019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 79092046-14b4-4b4e-9602-64761e2b6a56 · outbound

This paper cites PaRot: Patch-wise rotation- invariant network via feature disentanglement and pose restoration,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis PaRot: Patch-wise rotation- invariant network via feature disentanglement and pose restoration,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.618927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation df723204-2266-4ecd-9cac-4f4bc91a2495 · outbound

This paper cites Rotation-invariant local-to-global repre- sentation learning for 3D point cloud,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Rotation-invariant local-to-global repre- sentation learning for 3D point cloud,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.603769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e86ac0ad-927b-4f69-9179-509488f3b76f · outbound

This paper cites A closer look at rotation-invariant deep point cloud analysis,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis A closer look at rotation-invariant deep point cloud analysis,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.589043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1de4fe39-dd67-4c92-a760-125d34dff067 · outbound

This paper cites A functional approach to rotation equivariant non-linearities for Tensor Field Networks,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis A functional approach to rotation equivariant non-linearities for Tensor Field Networks,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.573083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation df3583da-a144-4c88-980e-0d6cd0855bd7 · outbound

This paper cites SE(3)-Transformers: 3D roto-translation equivariant attention networks,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis SE(3)-Transformers: 3D roto-translation equivariant attention networks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.557507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f1fae3e4-b8c4-4b78-91a9-162d8a32faff · outbound

This paper cites A rotation-invariant framework for deep point cloud anal- ysis,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis A rotation-invariant framework for deep point cloud anal- ysis,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.541553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0fce5109-7243-45a2-bb67-bbee5230ee88 · outbound

This paper cites Equivariant point cloud analysis via learning orientations for message passing,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Equivariant point cloud analysis via learning orientations for message passing,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.526802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b06c161a-8b2c-40a4-a09d-77fbb6bbfc54 · outbound

This paper cites PointNet: Deep learning on point sets for 3D classification and segmentation,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis PointNet: Deep learning on point sets for 3D classification and segmentation,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.509777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c733fa45-446a-4184-802e-f5ee045ca8cb · outbound

This paper cites PointNet++: Deep hierarchi- cal feature learning on point sets in a metric space,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis PointNet++: Deep hierarchi- cal feature learning on point sets in a metric space,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.492680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c4ceaf4a-6341-4c4e-a5b0-9a8ac1b7c82c · outbound

This paper cites PointNeXt: Revisiting PointNet++ with improved training and scaling strategies,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis PointNeXt: Revisiting PointNet++ with improved training and scaling strategies,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.475966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c682695c-17d9-4ee3-827d-1424947ea0f8 · outbound

This paper cites PCT: Point cloud transformer,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis PCT: Point cloud transformer,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.459353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5d0973c3-bc06-487a-b508-83abd7c49efa · outbound

This paper cites Walk in the cloud: Learning curves for point clouds shape analysis,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Walk in the cloud: Learning curves for point clouds shape analysis,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.443389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7916cc4d-c1e7-4618-a418-44a7f31990fd · outbound

This paper cites Point transformer,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Point transformer,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.425043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 792c689b-e3ac-45e2-b02a-05c13d96f897 · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis ShapeNet: An Information-Rich 3D Model Repository

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T11:59:54.193897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31ff5552-5ad8-4e97-a216-1478c01e6d78 · outbound

This paper cites 3D ShapeNets: A deep representation for volumetric shapes,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis 3D ShapeNets: A deep representation for volumetric shapes,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.407703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2a3518b2-d26a-489b-bc71-d485b940ec75 · outbound

This paper cites Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.389991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9ef3b609-0633-4740-93e1-f7feefc369a2 · outbound

This paper cites Self-supervised few-shot learning on point clouds,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Self-supervised few-shot learning on point clouds,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.374170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8429a2c4-ac5b-444d-b377-f11b564f26fe · outbound

This paper cites Decoupled Weight Decay Regularization.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Decoupled Weight Decay Regularization

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T11:59:54.212370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ede3e51d-3941-4094-9643-362c5de02569 · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T11:59:54.217273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8c0694f-ed10-4f16-8ca5-f292c6391440 · outbound

This paper cites Dynamic graph CNN for learning on point clouds,.

HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis Dynamic graph CNN for learning on point clouds,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:59:54.356456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.