22 citations · 40 across the 7 of their papers we have counts for
7 papers
Multi-Resolution Active Learning of Fourier Neural Operators
Shibo Li, Xin Yu, Wei Xing +3
Fourier Neural Operator (FNO) is a popular operator learning framework. It not only achieves the state-of-the-art performance in many tasks, but also is efficient in training and p…
Batch Multi-Fidelity Active Learning with Budget Constraints
Shibo Li, Jeff M. Phillips, Xin Yu +2
Learning functions with high-dimensional outputs is critical in many applications, such as physical simulation and engineering design. However, collecting training examples for the…
Nonparametric Embeddings of Sparse High-Order Interaction Events
Zheng Wang, Yiming Xu, Conor Tillinghast +3
High-order interaction events are common in real-world applications. Learning embeddings that encode the complex relationships of the participants from these events is of great imp…
A Self-Guided Framework for Radiology Report Generation
Jun Li, Shibo Li, Ying Hu +1
Automatic radiology report generation is essential to computer-aided diagnosis. Through the success of image captioning, medical report generation has been achievable. However, the…
Deep Multi-Fidelity Active Learning of High-dimensional Outputs
Shibo Li, Robert M. Kirby, Shandian Zhe
Many applications, such as in physical simulation and engineering design, demand we estimate functions with high-dimensional outputs. The training examples can be collected with di…
Analysis of Multivariate Scoring Functions for Automatic Unbiased Learning to Rank
Tao Yang, Shikai Fang, Shibo Li +2
Leveraging biased click data for optimizing learning to rank systems has been a popular approach in information retrieval. Because click data is often noisy and biased, a variety o…
Multi-Fidelity Bayesian Optimization via Deep Neural Networks
Shibo Li, Wei Xing, Mike Kirby +1
Bayesian optimization (BO) is a popular framework to optimize black-box functions. In many applications, the objective function can be evaluated at multiple fidelities to enable a…