Results 151 to 160 of about 1,626 (283)
Bayesianism without Learning [PDF]
According to the standard definition, a Bayesian agent is one who forms his posterior belief by conditioning his prior belief on what he has learned, that is, on facts of which he has become certain.
Dov Samet
core
Advanced Science, EarlyView.Oligosaccharides with defined glycosidic bonds drive divergent gut microbial succession and shape unique metabolic profiles. Absolute time‐series profiling with Bayesian generalized Lotka–Volterra modeling identifies bond‐specific microbial responders, while monoculture validation and metaproteomics reveal linkage‐matched transport and cleavage modules.
Xiaoxuan Lu +10 more
wiley +1 more source
Statistical primer: an introduction into the principles of Bayesian statistical analyses in clinical trials. [PDF]
Eur J Cardiothorac SurgHeuts S +5 more
europepmc +1 more source
Advanced Science, EarlyView.Non‐canonical amino acids (ncAAs) enhance peptide therapeutics but remain difficult to model computationally. SinCAA, a similarity‐enhanced pretraining framework, jointly optimizes contrastive learning guided by a novel conformational similarity metric with masked node reconstruction, capturing both functional relationships and chemical identity of ...
Chencheng Xu +8 more
wiley +1 more source
MXene‐Based Room‐Temperature NO2 Gas Sensors: A Meta‐Analysis
Advanced Science, EarlyView.This study presents the first comprehensive meta‐analysis of MXene‐based NO2 sensors, decoding 32 study characteristics across 61 peer‐reviewed studies. By isolating materials chemistry as the primary performance driver over device‐level parameters, the authors establish a methodological blueprint and a predictive structure–function map to accelerate ...
Alexander Khort +3 more
wiley +1 more source
NeuroQ: Quantum-Inspired Brain Emulation. [PDF]
Biomimetics (Basel)Vallverdú J, Rius G.
europepmc +1 more source
Probabilistic Computing via Gate‐Tunable Random Telegraph Noise
Advanced Science, EarlyView.Intrinsic random telegraph noise in metal–oxide–semiconductor field‐effect transistors is harnessed to create gate‐tunable probabilistic bits. By modulating carrier‐trapping dynamics, the device produces stochastic binary outputs with a continuous bias‐to‐probability transfer.
Gyungwon Yun +8 more
wiley +1 more source