AI model accelerates defect-based material design

Across the physical world, many intricate structures form via symmetry breaking. When a system with inherent symmetry ...

Mugen3D Launch Marks Tipping Point for World Model Applications

SILICON VALLEY - Jan. 22, 2026 - AI technology firm SumeruAI today announced the official launch of Mugen3D, a ...
Interesting Engineering

New adaptive system lets robots replicate human touch with far less training data

Japanese researchers develop an adaptive robot motion system that enables human-like grasping using minimal training data.
Tech Xplore

Adaptive motion system helps robots achieve human-like dexterity with minimal data

Despite rapid robotic automation advancements, most systems struggle to adapt their pre-trained movements to dynamic ...
Bdcnetwork.com

Reinventing the energy modeling process with AI

This blog post was authored by Mo Elsayed Senior Associate and Senior Building Performance Analyst, Page; Jill Kurtz, LEED AP BD+ C, Principal and Director of Building Sciences, Page; and Justin ...
Scientific Research Publishing

Rasmussen, C.E. and Williams, C.K.I. (2005) Gaussian Processes for Machine Learning. The MIT Press.

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...
IEEE

Periodic Gaussian Process Controlled B-Spline for Scalable Modeling of Irregularly Spaced Signals

Abstract: Existing periodic Gaussian process (PGP) modeling methods rely on the regularly-spaced-signal assumption (i.e., signals are evenly spaced) and the integer-period assumption for the sake of ...
EurekAlert!

sPGGM: a sample-perturbed Gaussian graphical model for identifying pre-disease stages and signaling molecules of disease progression

(a) Disease progression can be classified into three states: the normal stage, pre-disease stage and disease stage, with the pre-disease stage representing a critical threshold just before the onset ...
IEEE

Gaussian Process Latent Variable Modeling for Few-Shot Time Series Forecasting

Abstract: Accurate time series forecasting is crucial for optimizing resource allocation, industrial production, and urban management, particularly with the growth of cyber-physical and IoT systems.