From LLMs to hallucinations, here’s a simple guide to common AI terms

The rise of AI has brought an avalanche of new terms and slang. Here is a glossary with definitions of some of the most ...
Forbes

Machine Learning Trends For 2026

You're probably a little tired of reading or hearing about AI, right? Well, if that's the case, then you're in the right place because here, we're going to talk about machine learning (ML). Yes, it's ...
Phys.org

Mapping cell development with mathematics-informed machine learning

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions via a process called cell fate determination. The fate of individual cells, ...
Scientific Research Publishing

Mohammad-Djafari, A. (2021) Regularization, Bayesian Inference, and Machine Learning Methods for Inverse Problems. Entropy, 23, Article 1673.

ABSTRACT: Glioblastoma multiforme (GBM) remains one of the most aggressive brain malignancies, with a median survival of less than 15 months. This study advances glioblastoma multiforme (GBM) survival ...
VentureBeat

New ‘Test-Time Training’ method lets AI keep learning without exploding inference costs

A new study from researchers at Stanford University and Nvidia proposes a way for AI models to keep learning after deployment — without increasing inference costs. For enterprise agents that have to ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
GitHub

SmallML: Bayesian Transfer Learning for Small Data

Build production-grade machine learning models with just 50-200 observations per business entity. SmallML combines transfer learning, hierarchical Bayesian inference, and conformal prediction to ...
GitHub

mohansree14/Bayesian-Deep-Learning-for-Probabilistic-Financial-Forecasting

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...
VentureBeat

Together AI's ATLAS adaptive speculator delivers 400% inference speedup by learning from workloads in real-time

Enterprises expanding AI deployments are hitting an invisible performance wall. The culprit? Static speculators that can't keep up with shifting workloads. Speculators are smaller AI models that work ...
Scientific Research Publishing

Estimating Heterogeneous Treatment Effects of Early Childhood Interventions on Fifth-Grade Math Achievement: A Machine Learning-Augmented Causal Analysis of ECLS-K:2011 ()

School of Economics, The University of Nottingham-Ningbo, Ningbo, China. The study focuses on identifying and distinguishing whether there are differences between those students receiving special ...
ascopubs.org

Bayesian Counterfactual Machine Learning Individualizes Radiation Modality Selection to Mitigate Immunosuppression

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