Categories: AI/ML Research

Understanding the Role of Latent Space in Machine Learning Models

In this article, you will learn what latent spaces are and how they serve three distinct roles — descriptive, generative, and predictive — across a…

A Gentle Introduction to Multi-Head Latent Attention (MLA)

This post is divided into three parts; they are: • Low-Rank Approximation of Matrices • Multi-head Latent Attention (MLA) • PyTorch Implementation Multi-Head Attention (MHA) and Grouped-Query Attention (GQA) are the attention mechanisms used in almost all transformer models.

June 24, 2025

In "AI/ML Research"

Latent Temporal Flows for Multivariate Analysis of Wearables Data

Increased use of sensor signals from wearable devices as rich sources of physiological data has sparked growing interest in developing health monitoring systems to identify changes in an individual’s health profile. Indeed, machine learning models for sensor signals have enabled a diverse range of healthcare related applications including early detection…

October 25, 2022

In "FAANG"

Adapting Self-Supervised Representations as a Latent Space for Efficient Generation

We introduce Representation Tokenizer (RepTok), a generative modeling framework that represents an image using a single continuous latent token obtained from self-supervised vision transformers. Building on a pre-trained SSL encoder, we fine-tune only the semantic token embedding and pair it with a generative decoder trained jointly using a standard flow…

November 5, 2025

In "FAANG"

AI Generated Robotic Content