Researchers develop an AI-based platform that integrates reaction data with catalyst performance for the design of new ...

CatDRX is a generative AI framework developed at Institute of Science Tokyo, which enables the design of new chemical ...

CatDRX is a generative AI framework developed at Institute of Science Tokyo, which enables the design of new chemical catalysts based on the specific chemical reactions in which they are used. The ...

VANCOUVER, British Columbia--(BUSINESS WIRE)--Variational AI, the company behind Enki™, an advanced foundation model for small molecule drug discovery, today ...

Merck & Co. has doubled down on its partnership with Variational AI, striking a deal worth up to $349 million to collaborate on small molecule candidates against two targets. Variational disclosed a ...

Introduction: Thyroid nodule segmentation in ultrasound (US) images is a valuable yet challenging task, playing a critical role in diagnosing thyroid cancer. The difficulty arises from factors such as ...

Mexico will take on the United States in the 2025 Concacaf Gold final after beating Honduras in the semifinal on Wednesday. Raul Jimenez's second-half goal was all that El Tri needed to book yet ...

Quantum computing has gained significant attention in recent years, with numerous algorithms and applications under active development. Limited by the current quantum ...

1 Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran 2 College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, United Kingdom ...

Sparse autoencoders are central tools in analyzing how large language models function internally. Translating complex internal states into interpretable components allows researchers to break down ...

We designed a programmable quantum autoencoder on a silicon photonic chip with nearly no compression loss, which enabled us to propose and implement a new highly efficient error-correcting ...

Diffusion models generate images by progressively refining noise into structured representations. However, the computational cost associated with these models remains a key challenge, particularly ...