Forensic science plays a vital role in identifying, characterizing, and quantifying physical and biological traces recovered from crime scenes — a task that ...

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.

Olive oil and water do not naturally mix. Water molecules are polar, having a net electric dipole moment due to the bend ...

A study published in Nature Physics provides new molecular-level evidence from simulations that liquid water is not a single uniform substance, but a constantly shifting mixture of two distinct ...

The fundamental problem with recycling plastic through chemical breakdown has always been selectivity. When plastic is melted or heated, the result is a disorganised mix of gases, wax, tar, char, and ...

Logistic regression is a statistical method used to model binary outcome variables, such as whether a patient recovers or not, using a set of predictors. There are many competing methods for ...

Abstract: Data collected in modern industrial processes often exhibit complex non-Gaussian and multimodal characteristics. In order to address these problems, a robust mixture probabilistic partial ...

Air pollution has become a pressing challenge to global public health and environmental governance. Accurate analysis of pollutant concentrations critically depends on the completeness of monitoring ...

Abstract: Stochastic optimization aims to minimize the loss functions with noisy function and/or gradient measurements only. Depending on the types of the underlying variables, optimization problems ...

A mixture density network (MDN) Layer for Keras using pure Keras 3 operations. This makes it a bit more simple to experiment with neural networks that predict multiple real-valued variables that can ...

Managers are better equipped than ever to make good decisions. They are more aware that human judgment is fallible. They have oodles of data about their customers and products. They can use artificial ...