Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction | Paper Citation Record

Observation 307ad4e8-32b4-476d-befd-284f4fc2cac3 · outbound

This paper cites Intention-aware online pomdp planning for autonomous driving in a crowd,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Intention-aware online pomdp planning for autonomous driving in a crowd,

Reference 1

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Observation 1c433a05-a259-4921-8b4c-043fad2024ce · outbound

This paper cites Multimodal pedestrian trajectory prediction using probabilistic proposal network,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Multimodal pedestrian trajectory prediction using probabilistic proposal network,

Reference 2

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Observation 2e4d28a4-6cb0-4459-9b9f-d765673cb6c0 · outbound

This paper cites Reciprocal twin networks for pedestrian motion learning and future path prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Reciprocal twin networks for pedestrian motion learning and future path prediction,

Reference 3

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Observation e6e0ef2a-b4b5-4767-9dbd-fe14c39d397b · outbound

This paper cites Prediction of pedestrian crossing behavior based on surveillance video,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Prediction of pedestrian crossing behavior based on surveillance video,

Reference 4

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Observation 3f24e7c0-63a9-4254-9489-152634059a48 · outbound

This paper cites Trajectorycnn: a new spatio-temporal feature learning network for human motion prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Trajectorycnn: a new spatio-temporal feature learning network for human motion prediction,

Reference 5

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Observation d65bbc65-c2c6-42e3-9d37-caaba4ba0136 · outbound

This paper cites Exploring spatio–temporal graph convolution for video- based human–object interaction recognition,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Exploring spatio–temporal graph convolution for video- based human–object interaction recognition,

Reference 6

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Observation 6dfc8bf5-81ff-44ad-a394-504f4203a030 · outbound

This paper cites Sgcn: Sparse graph convolution network for pedestrian trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Sgcn: Sparse graph convolution network for pedestrian trajectory prediction,

Reference 7

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Observation 00cfdcb6-8ba9-4eb8-9eaf-1911daac5677 · outbound

This paper cites Multiclass-sgcn: Sparse graph- based trajectory prediction with agent class embedding,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Multiclass-sgcn: Sparse graph- based trajectory prediction with agent class embedding,

Reference 8

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Observation 4403e06b-648f-4e59-ad31-1662e527ff19 · outbound

This paper cites Social-bigat: Multimodal trajectory forecasting using bicycle-gan and graph attention networks,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Social-bigat: Multimodal trajectory forecasting using bicycle-gan and graph attention networks,

Reference 9

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Observation bd5c0688-82ab-4570-a8b9-c560b4e5f780 · outbound

This paper cites Stgat: Modeling spatial-temporal interactions for human trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Stgat: Modeling spatial-temporal interactions for human trajectory prediction,

Reference 10

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Observation 2c4de28b-ad08-4a07-9d4c-9e790be80cbd · outbound

This paper cites Social-stgcnn: A social spatio-temporal graph convolutional neural network for human trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Social-stgcnn: A social spatio-temporal graph convolutional neural network for human trajectory prediction,

Reference 11

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Observation 6919dd4d-e0f3-4c51-ab59-a24c66b9ffc0 · outbound

This paper cites Learning pedestrian group repre- sentations for multi-modal trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Learning pedestrian group repre- sentations for multi-modal trajectory prediction,

Reference 12

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Observation 7851724e-ee05-4cf2-8b9f-ab2a07221eff · outbound

This paper cites Eigentrajectory: Low-rank descriptors for multi-modal trajectory forecasting,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Eigentrajectory: Low-rank descriptors for multi-modal trajectory forecasting,

Reference 13

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Observation 0cf10ef6-b1f5-41d0-9f0c-0a7bfce9ac5b · outbound

This paper cites A set of control points conditioned pedestrian trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction A set of control points conditioned pedestrian trajectory prediction,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.237140Z

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Observation 41f878d8-8f11-4e51-9f49-0296fdfa08f6 · outbound

This paper cites Graph Attention Networks,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Graph Attention Networks,

Reference 15

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Observation 430910ee-ab81-4800-a91e-e71fba923ce0 · outbound

This paper cites Long short-term memory,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Long short-term memory,

Reference 16

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Observation 619da840-cdca-4bfc-ab97-9d5ddb06fb49 · outbound

This paper cites Semi-supervised classification with graph convolutional networks,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Semi-supervised classification with graph convolutional networks,

Reference 17

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Observation e1c9cf35-d3e5-42b6-a9a2-c262be01124f · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 18

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Observation e71f1c33-c79c-4cc3-9057-6142060bb88d · outbound

This paper cites Nodemixup: Tackling under-reaching for graph neural networks,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Nodemixup: Tackling under-reaching for graph neural networks,

Reference 19

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Observation 33768dd4-d79d-47ce-b366-f1b8165740fa · outbound

This paper cites Understanding over- squashing in gnns through the lens of effective resistance,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Understanding over- squashing in gnns through the lens of effective resistance,

Reference 20

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Observation 00994ed6-9ef6-472c-ae84-08090c02a911 · outbound

This paper cites Fully- connected spatial-temporal graph for multivariate time-series data,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Fully- connected spatial-temporal graph for multivariate time-series data,

Reference 21

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Observation 31ca2fdf-c965-4eaa-806c-3aff5d260f6f · outbound

This paper cites FourierGNN: Rethinking multivariate time series forecasting from a pure graph perspective,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction FourierGNN: Rethinking multivariate time series forecasting from a pure graph perspective,

Reference 22

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Observation 04275537-c399-4af7-8513-d885c6dd9e2a · outbound

This paper cites Groupnet: Multiscale hypergraph neural networks for trajectory prediction with relational reasoning,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Groupnet: Multiscale hypergraph neural networks for trajectory prediction with relational reasoning,

Reference 23

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Observation e18fa079-2180-42aa-ba55-f61d70f69273 · outbound

This paper cites Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Trajectory Prediction.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Trajectory Prediction

Reference 24

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Observation b6b961d7-c86d-43af-ab59-5bf970cd533a · outbound

This paper cites Deciphering spatio-temporal graph forecasting: A causal lens and treatment,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Deciphering spatio-temporal graph forecasting: A causal lens and treatment,

Reference 25

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Observation c933578c-bfe5-4bac-9760-8b55699b700e · outbound

This paper cites Heterogeneous graph convolutional neural network via hodge-laplacian for brain functional data,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Heterogeneous graph convolutional neural network via hodge-laplacian for brain functional data,

Reference 26

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Observation e8c39842-b2ee-418f-b27b-4722b2a75f29 · outbound

This paper cites Deep dual graph attention auto-encoder for community detection,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Deep dual graph attention auto-encoder for community detection,

Reference 27

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Observation 9c90ecbc-efd3-4270-8fc8-73dc143b5537 · outbound

This paper cites First-order operators and boundary triples,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction First-order operators and boundary triples,

Reference 28

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Observation 0f1743d0-7f35-42f3-8a2e-09449a4ba54d · outbound

This paper cites Attention is all you need,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Attention is all you need,

Reference 29

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Observation 96f5a4cf-4079-4ca1-a1e5-3f2cad96744d · outbound

This paper cites You’ll never walk alone: Modeling social behavior for multi-target tracking,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction You’ll never walk alone: Modeling social behavior for multi-target tracking,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.127914Z

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Observation b8be0f26-881e-4595-b4c1-7be17a8be52d · outbound

This paper cites Crowds by example,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Crowds by example,

Reference 31

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Observation ec4e5718-f74f-4342-9435-0e685abc67d8 · outbound

This paper cites Learning social etiquette: Human trajectory understanding in crowded scenes,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Learning social etiquette: Human trajectory understanding in crowded scenes,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.115280Z

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Observation 6d2435d3-d135-4d74-a71f-34500cb5d945 · outbound

This paper cites Social lstm: Human trajectory prediction in crowded spaces,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Social lstm: Human trajectory prediction in crowded spaces,

Reference 33

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Observation 7db22741-504d-41b7-b18b-490a2ea0fc1e · outbound

This paper cites Social gan: Socially acceptable trajectories with generative adversarial networks,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Social gan: Socially acceptable trajectories with generative adversarial networks,

Reference 34

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Observation 3ec7274f-abe9-43f5-8a50-84d224c285ee · outbound

This paper cites Geometric features informed multi-person human-object interaction recognition in videos,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Geometric features informed multi-person human-object interaction recognition in videos,

Reference 35

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Observation 480a977a-7cf5-4d9f-85b4-997e98ad7ab1 · outbound

This paper cites Spatial temporal graph convolutional networks for skeleton-based action recognition,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Spatial temporal graph convolutional networks for skeleton-based action recognition,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.086788Z

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Observation b49f8800-3b75-422d-adf3-79229fb65c5d · outbound

This paper cites Skeleton-based human ac- tion recognition via large-kernel attention graph convolutional network,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Skeleton-based human ac- tion recognition via large-kernel attention graph convolutional network,

Reference 37

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Observation 4c1bdaa8-deae-48ae-a13d-789882e47ec1 · outbound

This paper cites Multiphysical graph neural network (mp-gnn) for covid-19 drug design,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Multiphysical graph neural network (mp-gnn) for covid-19 drug design,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.070310Z

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Observation a1a32bc8-79fa-4cf0-a035-76e0c1084ffc · outbound

This paper cites Neural graph collaborative filtering,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Neural graph collaborative filtering,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.062367Z

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Observation b941f8f7-7a34-470d-afe6-b5d040b0652a · outbound

This paper cites Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.054233Z

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Observation e18a352b-fe1a-4b2f-9647-791c18291fe5 · outbound

This paper cites Trajectory unified transformer for pedestrian trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Trajectory unified transformer for pedestrian trajectory prediction,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.047043Z

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Observation 20d3dac6-e9b6-45f3-ae9c-95e1a7100f8d · outbound

This paper cites Uncovering the missing pattern: Unified framework towards trajectory imputation and prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Uncovering the missing pattern: Unified framework towards trajectory imputation and prediction,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.039343Z

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Observation 27dec39b-2654-49ff-8ae5-348dfb60c15e · outbound

This paper cites Mfan: Mixing feature attention network for trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Mfan: Mixing feature attention network for trajectory prediction,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.031080Z

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Observation 61dad6cc-43b9-495f-b387-8476d0b19b39 · outbound

This paper cites Socialvae: Human trajectory prediction using timewise latents,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Socialvae: Human trajectory prediction using timewise latents,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.024024Z

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Observation f0ac1135-052c-411e-a954-d9c10c2caaf3 · outbound

This paper cites Aut- ofocusing for synthetic aperture imaging based on pedestrian trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Aut- ofocusing for synthetic aperture imaging based on pedestrian trajectory prediction,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.016215Z

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Observation bb2c2707-edb2-426c-a434-46251a32fb27 · outbound

This paper cites Context-aware human trajectories prediction via latent variational model,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Context-aware human trajectories prediction via latent variational model,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.008966Z

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Observation ad013bea-6c0c-4bdc-8d8f-fe9be223f72c · outbound

This paper cites Mrgtraj: A novel non- autoregressive approach for human trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Mrgtraj: A novel non- autoregressive approach for human trajectory prediction,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:07.001515Z

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Observation e1543f24-2c2c-42bd-91af-d1e6eef4ad79 · outbound

This paper cites Pedestrian trajectory prediction using dynamics-based deep learning,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Pedestrian trajectory prediction using dynamics-based deep learning,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.994145Z

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Observation ce18d079-c348-4cdd-8e3f-8848d4ce59d3 · outbound

This paper cites Minimizing effective resistance of a graph,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Minimizing effective resistance of a graph,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.987221Z

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Observation 96a88f96-c1fb-40dc-9b7e-7d59736960a4 · outbound

This paper cites The moore–penrose inverse of the normalized graph lapla- cian,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction The moore–penrose inverse of the normalized graph lapla- cian,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.980059Z

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Observation 6dfda90a-d8f6-4cd1-8308-b628a9424201 · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Imagenet classification with deep convolutional neural networks,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.971763Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e6ccf175-1f8f-481e-9b2c-2de0f8970728 · outbound

This paper cites How Attentive are Graph Attention Networks?.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction How Attentive are Graph Attention Networks?

Reference 52

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Observation 9f07a5a1-3680-4b08-bdee-a86cc799ab07 · outbound

This paper cites Multi- stream representation learning for pedestrian trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Multi- stream representation learning for pedestrian trajectory prediction,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.963562Z

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Observation c653cda2-b02d-44b6-8d3c-bdaf703ab60b · outbound

This paper cites Autoregressive Image Generation without Vector Quantization.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Autoregressive Image Generation without Vector Quantization

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-09T11:59:06.764258Z

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Observation 524cb327-8e28-4314-b748-504baa4b13a6 · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-09T11:59:06.766838Z

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Observation 697f8ac6-af5d-475b-a528-6e13b41a3386 · outbound

This paper cites Social- implicit: Rethinking trajectory prediction evaluation and the effective- ness of implicit maximum likelihood estimation,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Social- implicit: Rethinking trajectory prediction evaluation and the effective- ness of implicit maximum likelihood estimation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.955640Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7fa620cc-7d0a-43b0-89e2-0410a038b387 · outbound

This paper cites Remember intentions: Retrospective-memory-based trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Remember intentions: Retrospective-memory-based trajectory prediction,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.947270Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 226edc5c-9c60-44fe-a6d2-c39f07cca434 · outbound

This paper cites Leapfrog diffusion model for stochastic trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Leapfrog diffusion model for stochastic trajectory prediction,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.940078Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a5221120-2ec2-4a0f-88b9-4d464b37cb7f · outbound

This paper cites Eqmotion: Equivariant multi-agent motion prediction with invariant interaction reasoning,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Eqmotion: Equivariant multi-agent motion prediction with invariant interaction reasoning,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.932507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dfb7fc0b-016d-4eb1-8883-c7db8e5c3816 · outbound

This paper cites Smemo: social memory for trajectory forecasting,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Smemo: social memory for trajectory forecasting,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.924990Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f23fe64d-cb8f-499b-8496-cdad23955845 · outbound

This paper cites Singulartrajectory: Universal trajec- tory predictor using diffusion model,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Singulartrajectory: Universal trajec- tory predictor using diffusion model,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.917585Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2c5e9af1-9706-495d-89f8-9e15ec68a0fe · outbound

This paper cites Higher- order relational reasoning for pedestrian trajectory prediction,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Higher- order relational reasoning for pedestrian trajectory prediction,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.909856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 20b79224-5356-4abe-9529-0d851ead0552 · outbound

This paper cites Adaptive trajectory prediction via transferable gnn,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Adaptive trajectory prediction via transferable gnn,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.901988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8a7fa034-1f38-4469-9a18-6a5a1a564db3 · outbound

This paper cites Inductive representation learning on large graphs,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Inductive representation learning on large graphs,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.893622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 70b2abd7-6b2f-49d2-a371-f036515a8140 · outbound

This paper cites Skeleton-based action recog- nition using sparse spatio-temporal gcn with edge effective resistance,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Skeleton-based action recog- nition using sparse spatio-temporal gcn with edge effective resistance,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.885671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2e622f9e-bf20-4a61-9004-92b0b9bd90cd · outbound

This paper cites Hdmixer: Hierarchical dependency with extendable patch for multivariate time series forecasting,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Hdmixer: Hierarchical dependency with extendable patch for multivariate time series forecasting,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.877981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b5f638f6-c38a-49c5-9ac9-db7c9b85d35a · outbound

This paper cites Flashattention: Fast and memory-efficient exact attention with io-awareness,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Flashattention: Fast and memory-efficient exact attention with io-awareness,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.869730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d217ed4e-44b2-4e5e-8f64-d884e1698492 · outbound

This paper cites Efficient transformers: A survey,.

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Efficient transformers: A survey,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:59:06.860328Z

Source-reported events for the cited work

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