Publications
*authors contributed equally.
#Uncertainty Quantification #Latent Variable Models #Dynamical Systems #Graph Learning #Sensors
2023
2022
- Uncertainty-Aware Meta-Learning for Multimodal Task DistributionsIn NeurIPS Workshop 2022
- A Large-Scale Ensemble Learning Framework for Demand ForecastingIn IEEE ICDM 2022 (Full Paper, Acceptance Rate: 9.77%)
- VQ-AR: Vector Quantized Autoregressive Probabilistic Time Series ForecastingarXiv preprint 2022
2021
- Distilling a hierarchical policy for planning and control via representation and reinforcement learningIn IEEE ICRA 2021
- A neural process approach for probabilistic reconstruction of no-data gaps in lunar digital elevation mapsAerospace Science and Technology 2021 [IF: 5.107]
- Bayesian Nonparametric State-Space Model for System Identification with Distinguishable Multimodal DynamicsJournal of Aerospace Information Systems 2021 [IF: 1.076]
- Online Gaussian Process State-Space Model: Learning and Planning for Partially Observable Dynamical SystemsInternational Journal of Control, Automation and Systems (accepted) [IF: 3.314]
- Global-Local Item Embedding for Temporal Set PredictionIn ACM RecSys Late-Breaking Results 2021
- AdamDGN: Adaptive Memory using Dynamic Graph Networks for Staleness Problem in Recommender SystemIn KDD Workshop 2021 (Spotlight)
- One4all User Representation for Recommender Systems in E-commercearXiv preprint 2021
2020
- A Worrying Analysis of Probabilistic Time-series Models for Sales ForecastingIn NeurIPS Workshop 2020
🏆 Best Poster Awards - Hop Sampling: A Simple Regularized Graph Learning for Non-Stationary EnvironmentsIn KDD Workshop 2020
- Multi-Manifold Learning for Large-scale Targeted Advertising SystemIn KDD Workshop 2020
- div2vec: Diversity-Emphasized Node EmbeddingIn ACM RecSys Workshop 2020
2019
- Tripartite heterogeneous graph propagation for large-scale social recommendationACM RecSys Late-Breaking Results 2019(presented in ICCV Workshop 2019 as well)
- InfoSSM: Interpretable Unsupervised Learning of Nonparametric State-Space Model for Multi-modal DynamicsIn AIAA Scitech 2019 Forum 2019
🏆 Student Paper Competition Finalists - A Bayesian Approach to Learning and Planning for Partially Observable Dynamical SystemsIn AIAA Scitech 2019 Forum 2019
2018
- Adaptive Path-Integral Autoencoders: Representation Learning and Planning for Dynamical SystemsIn NeurIPS 2018
- Deep gaussian process-based bayesian inference for contaminant source localizationIEEE Access 2018 [IF: 4.098]
- Deep Matrix-variate Gaussian ProcessesIn UAI Workshop 2018
- Efficient sensor network planning based on approximate potential gamesInternational Journal of Distributed Sensor Networks 2018 [IF: 1.787]
- High-resolution reconstruction for no data gaps in narrow angle camera digital terrain models using Gaussian process-latent variable modelIn Lunar and Planetary Science Conference 2018
- Resource Management for Active Track/TWS Interleaving in Airborne AESA RadarsIn Korea Institute of Military Science and Technology Annual Conference 2018
- Fuzzy Logic Approach for Target Prioritization in Airborne AESA RadarsIn Korean Society for Aeronautical and Space Sciences Annual Conference 2018
- Adaptive Radar Resource Managing Method Considering Hostile Airborne Targets in Air-to-Air and Air-to-Surface Interleaving ModeIn Korean Society for Aeronautical and Space Sciences Annual Conference 2018
2017
- Adaptive Radar Task Scheduling Algorithm Considering the Target PriorityIn Korean Society for Aeronautical and Space Sciences Annual Conference 2017
- Track Management for TWS mode of AESA RadarIn Korean Society for Aeronautical and Space Sciences Annual Conference 2017
2016
- Cooperative Sensing Planning of Distributed Sensor Networks for Multi-Target TrackingIn Korean Society for Aeronautical and Space Sciences Magazine 2016
🏆 KSAS Undergraduate Student Paper Competition (3rd Place)