Mathematical Foundations of Contrastive Loss
Explore the mathematical principles behind contrastive loss, InfoNCE, and supervised contrastive learning.
Recent Posts
Cross Entropy from First Principles
A derivation of binary cross entropy to showcase its mathematical foundation
Generating new samples with Variational Autoencoders
KL Divergence (Dipesh Dai) Limitations of Autoencoder (Suruchi) Variational Autoencoder Basic Architecture of Variational Autoencoder (Rajan) Loss of VAE...
Introduction to Autoencoder
Autoencoder Difference between generative and discriminative modelling Generative modelling Generative modelling is a statistical modeling technique that ...
Semantic Segmentation using U-Net
U-Net U-Net is a U-shaped encoder-decoder network architecture, which consists of four encoder blocks and four decoder blocks that are connected via bridge...