Anish HilaryBayesian Concepts (Part-1) : Probabilities and Statistical DistributionsI started learning Bayesian statistics to understand its role in uncertainty quantification. However, I quickly realized that I lacked an…6d ago6d ago
Anish HilaryCP Decomposition: Approximating Tensors using collection of VectorsImagine you’re trying to untangle a ball of yarn, where each strand represents a different piece of data. Tensors are like this ball of…Aug 13Aug 13
Anish HilaryCNN size reduction : Approximating Color Channels and Clustering higher layers.A technique to compress CNN model using SVDMay 30May 30
Anish HilaryLow rank Approximation for 4D kernels in Convolutional Neural Networks through SVDIn this blog post, we’ll explore a research paper that demonstrates the use of Singular Value Decomposition (SVD) to decompose 4D kernels…May 14May 14
Anish HilaryHow Fast-RCNN uses singular value decomposition(SVD) for fc-layer compression?Ever wondered how large sized neural networks are squeezed down to reduce the memory space occupied by the model?? One of the popular deep…May 6May 6
Anish HilaryBrief explanation on Matrix properties : facilitating Eigen & Spectral Decomposition“We’re diving into the world of reducing model complexity and speeding up computations. By understanding different matrix properties, we…Apr 30Apr 30
Anish HilaryUnderstanding Eigenvalues and Eigenvectors: Enabling Deep Neural Network CompressionEigenvalues and Eigenvectors are fundamental concepts in linear algebra, widely utilized across diverse domains. In the context of deep…Apr 18Apr 18