Publications
*authors contributed equally.
#Uncertainty Quantification #Latent Variable Models #Dynamical Systems #Graph Learning #Sensors
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]
2019
- 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
- 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