Results 91 to 100 of about 3,014,362 (294)
Modeling Uncertainty for Gaussian Splatting
IEEE Transactions on Neural Networks and Learning SystemsWe present Stochastic Gaussian Splatting (SGS): the first framework for uncertainty estimation using Gaussian Splatting (GS). GS recently advanced the novel-view synthesis field by achieving impressive reconstruction quality at a fraction of the computational cost of Neural Radiance Fields (NeRF).
Aira Luca Savant +2 more
openaire +4 more sources
Digital twins to accelerate target identification and drug development for immune‐mediated disorders
FEBS Open Bio, EarlyView.Digital twins integrate patient‐derived molecular and clinical data into personalised computational models that simulate disease mechanisms. They enable rapid identification and validation of therapeutic targets, prediction of drug responses, and prioritisation of candidate interventions.
Anna Niarakis, Philippe Moingeon
wiley +1 more source
IEEE Access, 2018 Kalman filters (KFs) and dynamic observers are two main classes of the dynamic state estimation (DSE) routines. The Power system DSE has been implemented by various KFs, such as the extended KF (EKF) and the unscented KF (UKF).
Junjian Qi, Ahmad F. Taha, Jianhui Wang
doaj +1 more source
Model uncertainty and its impact on the pricing of derivative instruments [PDF]
Model uncertainty, in the context of derivative pricing, can be defined as the uncertainty on the value of a contingent claim resulting from the lack of precise knowledge of the pricing model to be used for its valuation. We introduce here a quantitative
Rama Cont
core
FEBS Open Bio, EarlyView.5‐Aminolevulinic acid combined with ferric ammonium citrate (5‐ALA/FAC) stimulates dermal papilla cell activity and promotes hair follicle growth. The treatment enhances ERK and AKT signaling, increases hair‐inductive gene expression, and restores dermal papilla function suppressed by dihydrotestosterone and oxidative stress, resulting in enhanced hair
Han‐Wook Ryu, Eok‐Soo Oh, Sewoon Kim
wiley +1 more source
A Model-Based Reliability Metric Considering Aleatory and Epistemic Uncertainty
IEEE Access, 2017 Model-based reliability analysis and assessment methods rely on models, which are assumed to be precise, to predict reliability. In practice, however, the precision of the model cannot be guaranteed due to the presence of epistemic uncertainty.
Zhiguo Zeng +3 more
doaj +1 more source
Robust Control: A Note on the Timing of Model Uncertainty [PDF]
In this note a one-state, one-control variable quadratic linear problem with robust control and discount factor is developed to examine the optimal response of the first-period control to changes in future model uncertainty.
Arnulfo Rodriguez
core
Systemic dysregulation of apolipoproteins in amyotrophic lateral sclerosis serum
FEBS Open Bio, EarlyView.Amyotrophic lateral sclerosis (ALS) is a fatal disease that damages motor neurons. This study found that people with ALS show significant changes in blood fats and the proteins that carry them. Several apolipoproteins were higher, lipid balances were altered, and normal protein–lipid relationships were disrupted.
Finula I. Isik +6 more
wiley +1 more source
SensorsPractical robotic systems require control methods that remain reliable under limited computational resources, uncertain environments, and frequent changes in operating conditions.
Jangyeon Park, Kwanho Yu, Jungsu Choi
doaj +1 more source
FEBS Open Bio, EarlyView.Bioscience students were asked for their opinions on the value and teaching of skills. 204 responded that teamwork, time management and study skills are necessary to reach University, that scientific writing, research, laboratory and presentation skills are taught effectively during their studies, while other skills are gained inherently through study ...
Janella Borrell, Susan Crennell
wiley +1 more source