Three funds filed to let software run the portfolio. The sales pages promise a lot. The risk pages quietly take most of it back.

This manuscript represents a valuable contribution to understanding motion processing in the visual cortex. Based on a heterogeneous collection of previous empirical findings, the authors show that ...

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

Neither Sakana AI nor its external AI service providers will use customer data or inputs for model training or fine-tuning ...

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 ...

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 ...

Bloomberg is pleased to announce the newest cohort of three early-career researchers who have received the Bloomberg Data Science Ph.D. Fellowship for 2024-2025. Now in its seventh cohort, the ...

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 ...

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 ...

Machine learning (ML) algorithms are at the core of many modern technologies, from recommendation systems to self-driving cars. One of the key factors that determine the efficiency and scalability of ...

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 ...