AI inference provider Baseten reportedly raising $1.5B in funding

Baseten Inc., a startup with a platform for running artificial intelligence inference workloads, is raising $1.5 billion in ...
Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

The Algorithm That Counted On No One Appealing

A federal court ordered UnitedHealth to reveal how its nH Predict claims algorithm worked. The lawsuit’s real story is the ...
IEEE

Novel Bayesian Inference Algorithms for Multiuser Detection in M2M Communications

Abstract: The fifth generation and future wireless networks are expected to support massive machine-to-machine (M2M) communications. Due to the sporadic nature, massive M2M communications can be well ...
Scientific Research Publishing

A Bayesian-Inspired Framework for Parameter Estimation and Error Quantification ()

1 Dual Analytics, Geistthal-Södingberg, Austria. 2 Chair of Mathematics and Statistics, Montanuniversität Leoben, Leoben, Austria. 3 Materials Center Leoben Forschung GmbH, Leoben, Austria. 4 ...
IEEE

Variational Bayesian Inference Algorithms for Infinite Relational Model of Network Data

Abstract: Network data show the relationship among one kind of objects, such as social networks and hyperlinks on the Web. Many statistical models have been proposed for analyzing these data. For ...
GitHub

PyVBMC: Variational Bayesian Monte Carlo in Python

PyVBMC is a Python implementation of the Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference, previously implemented in MATLAB. VBMC is an approximate inference method ...
PNAS

Efficient Bayesian inference under the multispecies coalescent with migration

Inference of gene flow using genomic data requires powerful methods as the process of coalescent, migration, and mutation is highly stochastic. However, it is challenging to implement the multispecies ...