39 citations · 55 across the 10 of their papers we have counts for
3 papers · 1 filter
Staying on Track: Efficient Trajectory Discovery with Adaptive Batch Sampling
Arindam Fadikar, Abby Stevens, Mickael Binois +3
Bayesian optimization (BO) is a powerful framework for estimating parameters of expensive simulation models, particularly in settings where the likelihood is intractable and evalua…
Scalable Statistical Inference of Photometric Redshift via Data Subsampling
Arindam Fadikar, Stefan M. Wild, Jonas Chaves-Montero
Handling big data has largely been a major bottleneck in traditional statistical models. Consequently, when accurate point prediction is the primary target, machine learning models…
Analyzing Stochastic Computer Models: A Review with Opportunities
Evan Baker, Pierre Barbillon, Arindam Fadikar +10
In modern science, computer models are often used to understand complex phenomena, and a thriving statistical community has grown around analyzing them. This review aims to bring a…