Jinkyoo Park

IISE Trans., 2021

Continuous-Depth Neural Models for Dynamic Graph Prediction.

[BibT_eX]

[DOI]

CoRR, 2021

ScheduleNet: Learn to solve multi-agent scheduling problems with reinforcement learning.

[BibT_eX]

[DOI]

Junyoung Park

Sanjar Bakhtiyar

CoRR, 2021

Learning to schedule job-shop problems: Representation and policy learning using graph neural network and reinforcement learning.

[BibT_eX]

[DOI]

CoRR, 2021

A Hypergraph Convolutional Neural Network for Molecular Properties Prediction using Functional Group.

[BibT_eX]

[DOI]

Fangying Chen

Junyoung Park

CoRR, 2021

Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Differentiable Multiple Shooting Layers.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Collaborative Policies to Solve NP-hard Routing Problems.

[BibT_eX]

[DOI]

Minsu Kim

Joungho Kim

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Semi-supervised Bearing Fault Diagnosis with Adversarially-Trained Phase-Consistent Network.

[BibT_eX]

[DOI]

Jaehyuk Yi

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Cooperative and Competitive Biases for Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

Demand-Side Management With Shared Energy Storage System in Smart Grid.

[BibT_eX]

[DOI]

Jaeyeon Jo

IEEE Trans. Smart Grid, 2020

Hierarchical Anomaly Detection Using a Multioutput Gaussian Process.

[BibT_eX]

[DOI]

Woojin Cho

Youngrae Kim

IEEE Trans Autom. Sci. Eng., 2020

Count-based change point detection via multi-output log-Gaussian Cox processes.

[BibT_eX]

[DOI]

Joonho Bae

IISE Trans., 2020

TorchDyn: A Neural Differential Equations Library.

[BibT_eX]

[DOI]

CoRR, 2020

Approximate Inference for Spectral Mixture Kernel.

[BibT_eX]

[DOI]

Yohan Jung

Kyungwoo Song

CoRR, 2020

Stable Neural Flows.

[BibT_eX]

[DOI]

CoRR, 2020

Scalable Hybrid HMM with Gaussian Process Emission for Sequential Time-series Data Clustering.

[BibT_eX]

[DOI]

Yohan Jung

CoRR, 2020

Hypersolvers: Toward Fast Continuous-Depth Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Dissecting Neural ODEs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Hypergraph Convolutional Recurrent Neural Network.

[BibT_eX]

[DOI]

Jaehyuk Yi

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Multi-Agent Actor-Critic with Hierarchical Graph Attention Network.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Graph Neural Ordinary Differential Equations.

[BibT_eX]

[DOI]

CoRR, 2019

WATTNet: Learning to Trade FX via Hierarchical Spatio-Temporal Representation of Highly Multivariate Time Series.

[BibT_eX]

[DOI]

Michael Poli

Ilija Ilievski

CoRR, 2019

Scalable and transferable learning of algorithms via graph embedding for multi-robot reward collection.

[BibT_eX]

[DOI]

CoRR, 2019

Port-Hamiltonian Approach to Neural Network Training.

[BibT_eX]

[DOI]

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Idle Vehicle Rebalancing in Semiconductor Fabrication Using Factorized Graph Neural Network Reinforcement Learning.

[BibT_eX]

[DOI]

Kyuree Ahn

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018

Multi-Agent Actor-Critic with Generative Cooperative Policy Network.

[BibT_eX]

[DOI]

CoRR, 2018

Deep Reinforcement Learning with Fully Convolutional Neural Network to Solve an Earthwork Scheduling Problem.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

Data Driven Analytics (Machine Learning) for System Characterization, Diagnostics and Control Optimization.

[BibT_eX]

[DOI]

Max Ferguson

Proceedings of the Advanced Computing Strategies for Engineering, 2018

2016

Bayesian Ascent: A Data-Driven Optimization Scheme for Real-Time Control With Application to Wind Farm Power Maximization.

[BibT_eX]

[DOI]

IEEE Trans. Control. Syst. Technol., 2016

Classification of Heart Sound Recordings Using Convolution Neural Network.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, CinC 2016, Vancouver, 2016

Evaluation of a PMML-based GPR scoring engine on a cloud platform and microcomputer board for smart manufacturing.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

A data-driven approach for cooperative wind farm control.

[BibT_eX]

[DOI]

Soon-Duck Kwon

Proceedings of the 2016 American Control Conference, 2016

2015

Analyzing the Temporal Variation of Wind Turbine Responses Using Gaussian Mixture Model and Gaussian Discriminant Analysis.

[BibT_eX]

[DOI]

J. Comput. Civ. Eng., 2015

Erratum for "Analyzing the Temporal Variation of Wind Turbine Responses Using Gaussian Mixture Model and Gaussian Discriminant Analysis" by J. Park, K. Smarsly, K. H. Law, and D. Hartmann.

[BibT_eX]

[DOI]

J. Comput. Civ. Eng., 2015

Real-time energy prediction for a milling machine tool using sparse Gaussian process regression.

[BibT_eX]

[DOI]