5 citations · 16 across the 8 of their papers we have counts for
8 papers
Unveiling hidden features of social evolution by inferring Langevin dynamics from data
Youngkyoung Bae, Hajime Shimao, Seungwoong Ha +2
Are there hidden dynamical common patterns in the evolution of social and cultural history? While the growing availability of digitized social data invites us to answer this questi…
Dynamics of collective minds in online communities
Seungwoong Ha, Henrik Olsson, Kresimir Jaksic +2
Collective discourse and action are driven by collective minds. These shared semantic representations and related processes shape societal responses to critical societal challenges…
Interpretable Machine Learning in Physics: A Review
Sebastian Johann Wetzel, Seungwoong Ha, Raban Iten +2
Machine learning is increasingly transforming various scientific fields, enabled by advancements in computational power and access to large data sets from experiments and simulatio…
Inferring the Langevin Equation with Uncertainty via Bayesian Neural Networks
Youngkyoung Bae, Seungwoong Ha, Hawoong Jeong
Pervasive across diverse domains, stochastic systems exhibit fluctuations in processes ranging from molecular dynamics to climate phenomena. The Langevin equation has served as a c…
Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network
Seungwoong Ha, Hawoong Jeong
Dynamical systems with interacting agents are universal in nature, commonly modeled by a graph of relationships between their constituents. Recently, various works have been presen…
Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learning
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? Here, we addr…
Discovering conservation laws from trajectories via machine learning
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 an…
Deep learning reveals hidden interactions in complex systems
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 convention…