Coping With Simulators That Don't Always Return
Deterministic models are approximations of reality that are easy to interpret and often easier to build than stochastic alternatives. Unfortunately, as nature is capricious, observational data can never be fully explained by deterministic models in practice. Observation and process noise need to be added to adapt deterministic models to behave stochastically, such that they are capable of explaining and extrapolating from noisy data. We investigate and address computational inefficiencies that arise from adding process noise to deterministic simulators that fail to return for certain inputs; a property we describe as "brittle." We show how to train a conditional normalizing flow to propose perturbations such that the simulator succeeds with high probability, increasing computational efficiency.
Code (1)
Tasks
Computational EfficiencySimilar Papers 제목 키워드 기반
Coping With Simulators That Don’t Always Return
Deterministic models are approximations of reality that are often easier to build and interpret than stochastic alternatives. Unfortunately, as nature is capricious, observational data can never be fully explained by d…
Computational EfficiencySensor Data Simulation for Anomaly Detection of the Elderly Living Alone
With the increase of the number of elderly people living alone around the world, there is a growing demand for sensor-based detection of anomalous behaviors. Although smart homes with ambient sensors could be useful for …
Anomaly DetectionTransport away your problems: Calibrating stochastic simulations with optimal transport
Stochastic simulators are an indispensable tool in many branches of science. Often based on first principles, they deliver a series of samples whose distribution implicitly defines a probability measure to describe the p…
Introducing Instruction-Accurate Simulators for Performance Estimation of Autotuning Workloads
Accelerating Machine Learning (ML) workloads requires efficient methods due to their large optimization space. Autotuning has emerged as an effective approach for systematically evaluating variations of implementations. …
CORE-T: COherent REtrieval of Tables for Text-to-SQL
Realistic text-to-SQL workflows often require joining multiple tables. As a result, accurately retrieving the relevant set of tables becomes a key bottleneck for end-to-end performance. We study an open-book setting wher…