Helsinki

Multi-source probabilistic inference

The Multi-source Probabilistic Inference (MUPI) research group studies statistical machine learning and artificial intelligence. We develop new methods and algorithms for coping with uncertainty in ...
IEEE

An Efficient Bayesian Inference for Geo-Electromagnetic Data Inversion Based on Surrogate Modeling With Adaptive Sampling DNN

Abstract: The conventional geo-electromagnetic data inversions are mostly based on gradient optimization methods. However, this type of method can only provide a single “optimal” inverse model under ...
IEEE

Adaptive Model Predictive Current Control for PMSM Drives Based on Bayesian Inference

Abstract: Fully utilizing artificial intelligence (AI) algorithms to develop more flexible and robust intelligent control methods is a current hot spot in research. To solve the parameter robustness ...
The Daily Galaxy on MSN

NASA Dawn data uncovers hidden freshness signals inside asteroid avalanches on Vesta

Asteroid Vesta’s battered surface is far from static, it quietly preserves the memory of past collapses, impacts, and ...
eLife

Frequency-dependent modulation of foveal contrast sensitivity by fine-scale exogenously triggered attention

Fine-scale exogenous attention within the foveola selectively enhances contrast gain at low-to-mid spatial frequencies while increasing response gain across a broad spatial frequency range.
BMJ Open

Protocol for the economic evaluation of integrated longitudinal public health interventions in a cluster randomised controlled trial setting: the healthy life trajectories ...

Introduction In 2021, globally, cardiometabolic diseases (CMDs) accounted for 35% of the 1.73 billion disability-adjusted life years (DALYs) attributed to non-communicable diseases. The Healthy Life ...