Sat 6:15 a.m. - 6:30 a.m.
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Opening Remarks
(
Opening Remarks
)
>
SlidesLive Video
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🔗
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Sat 6:30 a.m. - 6:45 a.m.
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Continuous-time Graph Representation with Sequential Survival Process
(
Spotlight Talk
)
>
SlidesLive Video
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🔗
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Sat 6:45 a.m. - 7:00 a.m.
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Deep Graph Kernel Point Processes
(
Spotlight Talk
)
>
SlidesLive Video
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🔗
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Sat 7:00 a.m. - 7:30 a.m.
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Keynote: Daniele Zambon
(
Keynote
)
>
SlidesLive Video
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Daniele Zambon
🔗
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Sat 7:30 a.m. - 8:00 a.m.
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Keynote: Ingo Scholtes
(
Keynote
)
>
SlidesLive Video
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Ingo Scholtes
🔗
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Sat 8:00 a.m. - 8:30 a.m.
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Coffee Break
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🔗
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Sat 8:30 a.m. - 8:45 a.m.
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SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks
(
Spotlight Talk
)
>
SlidesLive Video
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🔗
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Sat 8:45 a.m. - 9:00 a.m.
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GenTKG: Generative Forecasting on Temporal Knowledge Graph
(
Spotlight Talk
)
>
SlidesLive Video
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🔗
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Sat 9:00 a.m. - 10:00 a.m.
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Poster Session
(
Poster Session
)
>
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🔗
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Sat 10:00 a.m. - 11:30 a.m.
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Lunch Break
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🔗
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Sat 11:30 a.m. - 12:00 p.m.
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Keynote: Rex Ying
(
Keynote
)
>
SlidesLive Video
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Rex Ying
🔗
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Sat 12:00 p.m. - 12:30 p.m.
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Keynote: Marinka Zitnik
(
Keynote
)
>
SlidesLive Video
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Marinka Zitnik
🔗
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Sat 12:30 p.m. - 1:00 p.m.
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Keynote: Kelsey Allen
(
Keynote
)
>
SlidesLive Video
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Kelsey Allen
🔗
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Sat 1:00 p.m. - 1:30 p.m.
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Coffee Break
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🔗
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Sat 1:30 p.m. - 2:15 p.m.
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Round Table Discussion
(
Discussion
)
>
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🔗
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Sat 2:15 p.m. - 3:15 p.m.
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Panel Discussion
(
Discussion Panel
)
>
SlidesLive Video
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🔗
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Sat 3:15 p.m. - 3:30 p.m.
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Closing Remarks
(
Closing Remarks
)
>
SlidesLive Video
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🔗
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-
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Effective Non-Dissipative Propagation for Continuous-Time Dynamic Graphs
(
Poster
)
>
link
SlidesLive Video
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Alessio Gravina · Giulio Lovisotto · Claudio Gallicchio · Davide Bacciu · Claas Grohnfeldt
🔗
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-
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Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting
(
Poster
)
>
link
SlidesLive Video
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Andrea Cini · Danilo Mandic · Cesare Alippi
🔗
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-
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Predicting COVID-19 pandemic by spatio-temporal graph neural networks: A New Zealand's study
(
Poster
)
>
link
SlidesLive Video
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Bach Nguyen · Truong Son Hy · Long Tran-Thanh · Nhung Nghiem
🔗
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-
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DspGNN: Bringing Spectral Design to Discrete Time Dynamic Graph Neural Networks for Edge Regression
(
Poster
)
>
link
SlidesLive Video
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Leshanshui Yang · Clement Chatelain · Sébastien Adam
🔗
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-
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Continuous-time Graph Representation with Sequential Survival Process
(
Poster
)
>
link
SlidesLive Video
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Abdulkadir Celikkanat · Nikolaos Nakis · Morten Mørup
🔗
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-
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Using Causality-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs
(
Poster
)
>
link
SlidesLive Video
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Franziska Heeg · Ingo Scholtes
🔗
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-
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Fast Temporal Wavelet Graph Neural Networks
(
Poster
)
>
link
SlidesLive Video
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Duc Thien Nguyen · Tuan Nguyen · Truong Son Hy · Risi Kondor
🔗
|
-
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Adaptive Message Passing Sign Algorithm
(
Poster
)
>
link
SlidesLive Video
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Changran Peng · Yi Yan · Ercan KURUOGLU
🔗
|
-
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GenTKG: Generative Forecasting on Temporal Knowledge Graph
(
Poster
)
>
link
SlidesLive Video
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Ruotong Liao · Xu Jia · Yunpu Ma · Volker Tresp
🔗
|
-
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Large-scale Graph Representation Learning of Dynamic Brain Connectome with Transformers
(
Poster
)
>
link
SlidesLive Video
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Byung-Hoon Kim · Jungwon Choi · EungGu Yun · Kyungsang Kim · Xiang Li · Juho Lee
🔗
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-
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SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks
(
Poster
)
>
link
SlidesLive Video
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Dingyi Zhuang · Yuheng Bu · Guang Wang · Shenhao Wang · Jinhua Zhao
🔗
|
-
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Leveraging Temporal Graph Networks Using Module Decoupling
(
Poster
)
>
link
SlidesLive Video
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Or Feldman · Chaim Baskin
🔗
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-
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Exploring Graph Structure in Graph Neural Networks for Epidemic Forecasting
(
Poster
)
>
link
SlidesLive Video
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Sai Supriya Varugunda · ChingHao Fan · Lijing Wang
🔗
|
-
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Gen-T: Reduce Distributed Tracing Operational Costs Using Generative Models
(
Poster
)
>
link
SlidesLive Video
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Saar Tochner · Giulia Fanti · Vyas Sekar
🔗
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-
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Do Temporal Knowledge Graph Embedding Models Learn or Memorize
(
Poster
)
>
link
SlidesLive Video
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Jiaxin Pan · Mojtaba Nayyeri · Yinan Li · Steffen Staab
🔗
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-
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Marked Neural Spatio-Temporal Point Process Involving a Dynamic Graph Neural Network
(
Poster
)
>
link
SlidesLive Video
|
Silvia Beddar-Wiesing · Alice Moallemy-Oureh · Rüdiger Nather · Josephine Thomas
🔗
|
-
|
Temporal graph models fail to capture global temporal dynamics
(
Poster
)
>
link
SlidesLive Video
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Michal Daniluk · Jacek Dabrowski
🔗
|
-
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Graph Kalman Filters
(
Poster
)
>
link
SlidesLive Video
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Daniele Zambon · Cesare Alippi
🔗
|
-
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A Generative Self-Supervised Framework using Functional Connectivity in fMRI Data
(
Poster
)
>
link
SlidesLive Video
|
Jungwon Choi · Seongho Keum · EungGu Yun · Byung-Hoon Kim · Juho Lee
🔗
|
-
|
Deep graph kernel point processes
(
Poster
)
>
link
SlidesLive Video
|
Zheng Dong · Matthew Repasky · Xiuyuan Cheng · Yao Xie
🔗
|
-
|
Topological and Temporal Data Augmentation for Temporal Graph Networks
(
Poster
)
>
link
SlidesLive Video
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Haoran Liu · Jianling Wang · Kaize Ding · James Caverlee
🔗
|
-
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Spatial-Temporal DAG Convolutional Networks for End-to-End Joint Effective Connectivity Learning and Resting-State fMRI Classification
(
Poster
)
>
link
SlidesLive Video
|
Rui Yang · Wenrui Dai · Huajun She · Yiping Du · Dapeng Wu · Hongkai Xiong
🔗
|
-
|
Hierarchical Joint Graph Learning and Multivariate Time Series Forecasting
(
Poster
)
>
link
|
JuHyeon Kim · HyunGeun Lee · Seungwon Yu · Ung Hwang · Wooyul Jung · Miseon Park · Kijung Yoon
🔗
|
-
|
Exploring Time Granularity on Temporal Graphs for Dynamic Link Prediction in Real-world Networks
(
Poster
)
>
link
SlidesLive Video
|
Xiangjian Jiang · Yanyi Pu
🔗
|
-
|
Inductive Link Prediction in Static and Temporal Graphs for Isolated Nodes
(
Poster
)
>
link
SlidesLive Video
|
Ayan Chatterjee · Robin Walters · Giulia Menichetti · Tina Eliassi-Rad
🔗
|
-
|
BitGraph: A Framework For Scaling Temporal Graph Queries on GPUs
(
Poster
)
>
link
SlidesLive Video
|
Alexandria Barghi
🔗
|
-
|
TBoost: Gradient Boosting Temporal Graph Neural Networks
(
Poster
)
>
link
SlidesLive Video
|
Pritam Kumar Nath · Govind Waghmare · Nancy Agrawal · Nitish Kumar · Siddhartha Asthana
🔗
|
-
|
Towards predicting future time intervals on Temporal Knowledge Graphs
(
Poster
)
>
link
SlidesLive Video
|
Roxana Pop · Egor Kostylev
🔗
|
-
|
STGraph: A Framework for Temporal Graph Neural Networks
(
Poster
)
>
link
SlidesLive Video
|
Nithin Manoj · Joel Mathew Cherian · Kevin Concessao · Unnikrishnan Cheramgalath
🔗
|
-
|
Anomaly Detection in Continuous-Time Temporal Provenance Graphs
(
Poster
)
>
link
SlidesLive Video
|
Jakub Reha · Giulio Lovisotto · Michele Russo · Alessio Gravina · Claas Grohnfeldt
🔗
|
-
|
DURENDAL: Graph deep learning framework for temporal heterogeneous networks
(
Poster
)
>
link
SlidesLive Video
|
Manuel Dileo · Matteo Zignani · Sabrina Gaito
🔗
|
-
|
Learning Temporal Higher-order Patterns to Detect Anomalous Brain Activity
(
Poster
)
>
link
|
Ali Behrouz · Farnoosh Hashemi
🔗
|
-
|
Mitigating Cold-start Problem using Cold Causal Demand Forecasting Model
(
Poster
)
>
link
SlidesLive Video
|
Zahra Fatemi · Minh Huynh · Elena Zheleva · Zamir Syed · Xiaojun Di
🔗
|
-
|
An Information-Theoretic Analysis on Temporal Graph Evolution
(
Poster
)
>
link
SlidesLive Video
|
Amirmohammad Farzaneh
🔗
|
-
|
Todyformer: Towards Holistic Dynamic Graph Transformers with Structure-Aware Tokenization
(
Poster
)
>
link
|
Mahdi Biparva · Raika Karimi · Faezeh Faez · Yingxueff Zhang
🔗
|