research
∙
10/23/2022
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks
Physics-informed neural networks (PINNs) are emerging as popular mesh-fr...
share
research
∙
09/12/2022
A novel learning-based robust model predictive control energy management strategy for fuel cell electric vehicles
The multi-source electromechanical coupling makes the energy management ...
research
∙
07/08/2022
Nonparametric Embeddings of Sparse High-Order Interaction Events
High-order interaction events are common in real-world applications. Lea...
research
∙
07/01/2022
Infinite-Fidelity Coregionalization for Physical Simulation
Multi-fidelity modeling and learning are important in physical simulatio...
research
∙
06/19/2022
A Self-Guided Framework for Radiology Report Generation
Automatic radiology report generation is essential to computer-aided dia...
research
∙
10/16/2021
Meta-Learning with Adjoint Methods
Model Agnostic Meta-Learning (MAML) is widely used to find a good initia...
research
∙
09/07/2021
Impatient PPSZ – a Faster algorithm for CSP
PPSZ is the fastest known algorithm for (d,k)-CSP problems, for most val...
research
∙
06/18/2021
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks
Bayesian optimization (BO) is a powerful approach for optimizing black-b...
research
∙
12/02/2020
Deep Multi-Fidelity Active Learning of High-dimensional Outputs
Many applications, such as in physical simulation and engineering design...
research
∙
08/20/2020
Analysis of Multivariate Scoring Functions for Automatic Unbiased Learning to Rank
Leveraging biased click data for optimizing learning to rank systems has...
research
∙
07/06/2020
Multi-Fidelity Bayesian Optimization via Deep Neural Networks
Bayesian optimization (BO) is a popular framework to optimize black-box ...
research
∙
03/25/2020