Search Results for author: Hawoong Jeong

Found 12 papers, 8 papers with code

Early onset of structural inequality in the formation of collaborative knowledge, Wikipedia

1 code implementation19 Oct 2016 Jinhyuk Yun, Sang Hoon Lee, Hawoong Jeong

We perform an in-depth analysis on the inequality in 863 Wikimedia projects.

Physics and Society Social and Information Networks

Historic Emergence of Diversity in Painting: Heterogeneity in Chromatic Distance in Images and Characterization of Massive Painting Data Set

no code implementations25 Jan 2017 Byunghwee Lee, Daniel Kim, Seunghye Sun, Hawoong Jeong, Juyong Park

Painting is an art form that has long functioned as a major channel for the creative expression and communication of humans, its evolution taking place under an interplay with the science, technology, and social environments of the times.

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

Learning entropy production via neural networks

2 code implementations9 Mar 2020 Dong-Kyum Kim, Youngkyoung Bae, Sangyun Lee, Hawoong Jeong

This Letter presents a neural estimator for entropy production, or NEEP, that estimates entropy production (EP) from trajectories of relevant variables without detailed information on the system dynamics.

Deep reinforcement learning for feedback control in a collective flashing ratchet

1 code implementation20 Nov 2020 Dong-Kyum Kim, Hawoong Jeong

A collective flashing ratchet transports Brownian particles using a spatially periodic, asymmetric, and time-dependent on-off switchable potential.

reinforcement-learning Reinforcement Learning (RL)

Inertial effects on the Brownian gyrator

no code implementations23 Dec 2020 Youngkyoung Bae, Sangyun Lee, Juin Kim, Hawoong Jeong

Another unique feature of the Langevin description is that rotation is maximized at a particular anisotropy while the stability of the rotation is minimized at a particular anisotropy or mass.

Statistical Mechanics

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

Attaining entropy production and dissipation maps from Brownian movies via neural networks

1 code implementation29 Jun 2021 Youngkyoung Bae, Dong-Kyum Kim, Hawoong Jeong

We show that our method accurately measures the EP and creates a dissipation map in two nonequilibrium systems, the bead-spring model and a network of elastic filaments.

Time Series Time Series Analysis

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 (RL)

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

Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning

no code implementations2 Dec 2022 Yeongwoo Song, Hawoong Jeong

While effective, these methods are limited to the system domain, where the type of system remains consistent and thus cannot ensure the adaptation to new, or unseen physical systems governed by different laws.

Domain Generalization Meta-Learning

Inferring the Langevin Equation with Uncertainty via Bayesian Neural Networks

no code implementations2 Feb 2024 Youngkyoung Bae, Seungwoong Ha, Hawoong Jeong

Pervasive across diverse domains, stochastic systems exhibit fluctuations in processes ranging from molecular dynamics to climate phenomena.

Cannot find the paper you are looking for? You can Submit a new open access paper.