Morning Overview on MSN

How DeepSeek’s new training method could disrupt advanced AI again

DeepSeek’s latest training research arrives at a moment when the cost of building frontier models is starting to choke off ...
Psychology Today

How AI Illuminates the Architecture of Personal Transformation

How do caterpillars keep memories after dissolving into soup? How do we transform without fragmenting? A new AI architecture ...
WinBuzzer

DeepSeek Unveils ‘mHC’ Architecture to Fix AI Training Instability Amid Chip Bans

DeepSeek has introduced Manifold-Constrained Hyper-Connections (mHC), a novel architecture that stabilizes AI training and ...
IEEE

Autoencoder Architectures for Low-Rate Sparse Point Cloud Geometry Coding

Abstract: Efficient compression of sparse point cloud geometry remains a critical challenge in 3D content processing, particularly for low-rate scenarios where conventional codecs struggle to maintain ...
GitHub

Variational autoencoder with Kolmogorov-Arnold Network for spatial domain detection.

Experiments were executed on NVIDIA A40 of 46068MiB memory in linux with torch==2.1.0+cu121, torch_geometric==2.3.1, torch-sparse==0.6.18+pt21cu121, and torchvision==0.16.0+cu121. The stkan is an ...
Scientific Research Publishing

Al-Qatf, M., Lasheng, Y., Al-Habib, M. and Al-Sabahi, K. (2018) Deep Learning Approach Combining Sparse Autoencoder with SVM for Network Intrusion Detection. IEEE Access, 6 ...

ABSTRACT: This work contributes to the development of intelligent data-driven approaches to improve intrusion management in smart IoT environments. The proposed model combines a hybrid ...
Scientific Research Publishing

Xu, J., Xiang, L., Liu, Q., Gilmore, H., Wu, J., Tang, J., et al. (2016) Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images. IEEE ...

ABSTRACT: Liver cancer is one of the most prevalent and lethal forms of cancer, making early detection crucial for effective treatment. This paper introduces a novel approach for automated liver tumor ...
IEEE

Online Public Opinion Situation Assessment by Deep Sparse Autoencoder and Time-Series Modeling Convolutional Neural Network

Abstract: We have developed an innovative framework for analyzing online public sentiment, referred to as the Online Public Opinion Situation Assessment (OPOSA) model. This model employs Deep Sparse ...