Search Results for author: Seungwoong Ha

Found 4 papers, 4 papers with code

Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network

1 code implementation28 Aug 2022 Seungwoong Ha, Hawoong Jeong

Our model employs a novel pairwise attention (PA) mechanism to refine the trajectory representations and a graph transformer to extract heterogeneous interaction weights for each pair of agents.

Trajectory Prediction

Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learning

1 code implementation26 Apr 2022 Seungwoong Ha, Hawoong Jeong

How have individuals of social animals in nature evolved to learn from each other, and what would be the optimal strategy for such learning in a specific environment?

reinforcement-learning reinforcement Learning

Discovering conservation laws from trajectories via machine learning

1 code implementation8 Feb 2021 Seungwoong Ha, Hawoong Jeong

Invariants and conservation laws convey critical information about the underlying dynamics of a system, yet it is generally infeasible to find them from large-scale data without any prior knowledge or human insight.

BIG-bench Machine Learning

Deep learning reveals hidden interactions in complex systems

1 code implementation3 Jan 2020 Seungwoong Ha, Hawoong Jeong

Rich phenomena from complex systems have long intrigued researchers, and yet modeling system micro-dynamics and inferring the forms of interaction remain challenging for conventional data-driven approaches, being generally established by human scientists.

Graph Attention

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