DeepSeek develops mHC AI architecture to boost model performance

DeepSeek researchers have developed a technology called Manifold-Constrained Hyper-Connections, or mHC, that can improve the performance of artificial intelligence models. The Chinese AI lab debuted ...

DeepSeek kicks off 2026 with paper signalling push to train bigger models for less

DeepSeek has published a technical paper co-authored by founder Liang Wenfeng proposing a rethink of its core deep learning ...
C&EN

Connecting Vibrational Spectroscopy to Atomic Structure via Supervised Manifold Learning: Beyond Peak Analysis

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. Article Views ...

Behold the Manifold, the Concept that Changed How Mathematicians View Space

In the mid-19th century, Bernhard Riemann conceived of a new way to think about mathematical spaces, providing the foundation ...
IEEE

Genetic Programming for Explainable Manifold Learning

Abstract: Manifold learning techniques play a pivotal role in machine learning by revealing lower-dimensional embeddings within high-dimensional data, thereby enhancing the efficiency, ...
Scientific Research Publishing

Belkin, M., Niyogi, P. and Sindhwani, V. (2006) Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples. Journal of Machine Learning ...

ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...
hcinnovationgroup

Q&A: Manifold CEO Vinay Seth Mohta on Building a Platform for Clinical Research

Manifold, a data platform startup company that supports clinical researchers, recently announced that the American Cancer Society (ACS) will leverage its platform to modernize its population research ...