New Adaptive Tensor Decomposition Method Boosts Temporal Data Modeling

CATTE uses learnable Fourier features for spatial indexes and neural ODEs for temporal dynamics, pruning components with a sparsity prior to improve accuracy on climate data. getnews.me/new-adaptive-tensor-deco... #cattte #tensordecomposition

Graph-Regularized Tensor Train for Better Visual Data Completion

Graph-regularized tensor-train avoids folding, keeping image layout intact. With a sparse Bayesian GIG prior, it boosts reconstruction accuracy and converges faster. getnews.me/graph-regularized-tensor... #graphregularization #tensordecomposition

Tensor Decompositions | Institute of Information Theory and Automation UTIA of the CAS is a public research institute focused on AI, signal processing, systems theory, and applied mathematics. It conducts top-level research, cooperates with universities, and contributes ...

How do we analyze high-dimensional data? At ÚTIA, we develop advanced tensor decomposition methods for efficient data modeling and inference.
🔗 utia.cas.cz/en/research/...
#TensorDecomposition #UTIA

Los Alamos AI Breakthrough Neutralizes Adversarial Attacks and Restores Trust in Neural Networks Los Alamos scientists unveil LoRID, a cutting-edge AI defense that wipes out adversarial threats without compromising data integrity—setting a new gold standard for secure and trustworthy neural...

Los Alamos AI Breakthrough Neutralizes Adversarial Attacks and Restores Trust in Neural Networks 🔐🤖⚙️ www.azoai.com/news/2025031... #AI #NeuralNetworks #Cybersecurity #MachineLearning #AdversarialAttacks #DiffusionModels #TensorDecomposition #Innovation #DataSecurity #Supercomputing