Financial markets are governed by a combination of rational and irrational forces, statistical probabilities and "animal ...

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

Abstract: Extreme learning machine (ELM) has become a popular topic in machine learning in recent years. ELM is a new kind of single-hidden layer feedforward neural network with an extremely low ...

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 ...

The behavior of language models is influenced by the prior context provided in prompts. Depending on whether you pick synthesis or shake, the next row looks very different — Vishal Misra Contextual ...

Baal is an active learning library that supports both industrial applications and research usecases. Read the documentation at https://baal.readthedocs.io. Our paper can be read on arXiv. It includes ...

Abstract: Multiple-instance learning (MIL) can solve supervised learning tasks, where only a bag of multiple instances is labeled, instead of a single instance. It is considerably important to develop ...

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...

Bayesian regression with linear basis function models. Introduction to Bayesian linear regression. Implementation with plain NumPy and scikit-learn. See also PyMC3 implementation. Gaussian processes.

Experimental variogram modelling is an essential process in geostatistics. The use of artificial intelligence (AI) is a new and advanced way of automating experimental variogram modelling. One part of ...