Search Results for author: Siew Kei Lam

Found 3 papers, 1 papers with code

Reinforced Continual Learning for Graphs

no code implementations4 Sep 2022 Appan Rakaraddi, Siew Kei Lam, Mahardhika Pratama, Marcus de Carvalho

Continual learning on graphs is largely unexplored and existing graph continual learning approaches are limited to the task-incremental learning scenarios.

Class Incremental Learning Graph Classification +1

Graph2Kernel Grid-LSTM: A Multi-Cued Model for Pedestrian Trajectory Prediction by Learning Adaptive Neighborhoods

1 code implementation3 Jul 2020 Sirin Haddad, Siew Kei Lam

Pedestrian trajectory prediction is a prominent research track that has advanced towards modelling of crowd social and contextual interactions, with extensive usage of Long Short-Term Memory (LSTM) for temporal representation of walking trajectories.

Pedestrian Trajectory Prediction Trajectory Prediction

Situation-Aware Pedestrian Trajectory Prediction with Spatio-Temporal Attention Model

no code implementations13 Feb 2019 Sirin Haddad, Meiqing Wu, He Wei, Siew Kei Lam

Pedestrian trajectory prediction is essential for collision avoidance in autonomous driving and robot navigation.

Autonomous Driving Collision Avoidance +3

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