Johns Hopkins Medicine

Machine Learning Model Improves Accuracy of Liquid Biopsy Results

A machine learning model developed by researchers at the Johns Hopkins Kimmel Cancer Center filters out the biological noise ...

Researchers trained an open source AI search agent, Harness-1, that outperforms GPT-5.4 on recalling relevant information

Harness-1 suggests that the future of agentic AI lies in building better environments for models to work within, rather than ...

Hidden geometry explains why kernel methods separate complex data so well

Are two sets of data genuinely different, or is it because of randomness? This question, known as the two-sample testing problem, becomes notoriously difficult in modern datasets, because they are ...
The Manila Times

WiMi Proposes a New High-Performance Fault-Tolerant Quantum Computing Technology Based on Multi-Hypercube Codes

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ('WiMi' or the 'Company'), a leading global Hologram Augmented Reality ('AR') Technology provider, proposes a new high-performance fault-tolerant quantum ...
Devdiscourse

Banks could strengthen credit card fraud screening with ensemble machine learning model

Read more about Banks could strengthen credit card fraud screening with ensemble machine learning model on Devdiscourse ...
TMCnet

WiMi Achieves Breakthrough in Deep Convolutional Neural Network Technology Based on Quantum Parameterized Circuits

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company") is a leading global Hologram Augmented Reality ("AR") Technology provider. A quantum deep convolutional neural network technology ...
IEEE

Feature Construction Using Network Control Theory and Rank Encoding for Graph Machine Learning

Abstract: In this article, we utilize the concept of average controllability in graphs, along with a novel rank encoding method, to enhance the performance of Graph Neural Networks (GNNs) in social ...
EurekAlert!

New quantum encoding methods slash circuit complexity in machine learning

This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms. All methods ...
PNAS

An encoding generative modeling approach to dimension reduction and covariate adjustment in causal inference with observational studies

Causal inference has been increasingly essential in modern observational studies with rich covariate information. However, it is often challenging to estimate the causal effect with high-dimensional ...