4 papers
Bootstrap Flow-Map Tree Sampling Enables Online Feedback Driven Search
Binglin Ji, Anindya Sarkar, Hengchang Lu +2
In many scientific and engineering domains, maximizing discovery within a limited sampling budget demands strategic, observation-guided exploration. While generative models have en…
Sequentially-Controlled Interactive Multi-Particle Flow-Maps for Online Feedback-Driven Search
Binglin Ji, Anindya Sarkar, Hengchang Lu +2
While generative models have enabled training-free reward alignment, current methods typically excel in local exploration within narrow regions of the underlying distribution. Thes…
Active Target Discovery under Uninformative Prior: The Power of Permanent and Transient Memory
Anindya Sarkar, Binglin Ji, Yevgeniy Vorobeychik
In many scientific and engineering fields, where acquiring high-quality data is expensive--such as medical imaging, environmental monitoring, and remote sensing--strategic sampling…
Online Feedback Efficient Active Target Discovery in Partially Observable Environments
Anindya Sarkar, Binglin Ji, Yevgeniy Vorobeychik
In various scientific and engineering domains, where data acquisition is costly--such as in medical imaging, environmental monitoring, or remote sensing--strategic sampling from un…