Study compares machine learning models of raindrop formation

Raindrops form inside clouds when tiny particles of water collide and stick together, forming larger droplets that eventually ...
Eos

Comparing Machine Learning Models of Raindrop Formation

Better simulations of raindrop formation could help improve climate and weather models. This newsletter rocks. Get the most ...
Communications of the ACM

Can We Understand How Large Language Models Reason?

Large language models can write essays, solve math problems, and generate computer code, but it’s not fully understood how ...

Corinex and Plexigrid team up to deliver the most accurate digital-twin solution for grid visibility and flexibility to date

Corinex Corp. and Plexigrid S.L. have signed a strategic cooperation agreement to market Corinex Plexigrid Intelligence, a ...
Thorax

Comparative performance of endobronchial ultrasound-guided sampling techniques in patients with mediastinal lesions: a network meta-analysis

Background Comparative evidence on the diagnostic yield of endobronchial ultrasound (EBUS)-guided sampling techniques for ...
PsyPost on MSN

An international brain imaging analysis reveals how psychedelics rewire neural circuits

An international analysis combining brain imaging data from multiple independent studies has identified a common pattern in ...
IEEE

Dynamic Bayesian Network Modeling, Learning, and Inference: A Survey

Abstract: Since the introduction of Dynamic Bayesian Networks (DBNs), their efficiency and effectiveness have increased through the development of three significant aspects: (i) modeling, (ii) ...
leewayhertz

Bayesian networks in AI: Role in machine learning, example, types and applications

Imagine a scenario where a team of doctors faces a perplexing medical puzzle. A patient shows a range of symptoms, each pointing to multiple possible diseases. How can they navigate this diagnostic ...
IEEE

Hierarchical Bayesian Network Modeling Framework for Large-Scale Process Monitoring and Decision Making

Abstract: In this brief, a hierarchical Bayesian network modeling framework is formulated for large-scale process monitoring and decision making, which includes a basic layer and a functional layer.
Science Daily

AI unravels the hidden communication of gut microbes

Scientists have turned to advanced AI to decode the intricate ecosystem of gut bacteria and their chemical signals. Using a Bayesian neural network called VBayesMM, researchers can now identify ...
Hacker

Understanding Bayesian Networks: A Graphical Model for Uncertainty

Bayesian Network (BN) [15] is a probabilistic graphical model that represents a set of random variables and their conditional probabilities via a directed acyclic graph (DAG). In these graphical ...
GitHub

Uncertainty-aware Bayesian neural network with SHAP interpretability.qmd

- Complex assembly systems such as diesel engines, CNC machine tools, and aircraft assembly are dynamic, multimodal, and data-imperfect environments. - Small upstream deviations accumulate across ...