23 citations · 25 across the 5 of their papers we have counts for
5 papers
TreeSeg: Hierarchical Topic Segmentation of Large Transcripts
Dimitrios C. Gklezakos, Timothy Misiak, Diamond Bishop
From organizing recorded videos and meetings into chapters, to breaking down large inputs in order to fit them into the context window of commoditized Large Language Models (LLMs),…
Active Predictive Coding: A Unified Neural Framework for Learning Hierarchical World Models for Perception and Planning
Rajesh P. N. Rao, Dimitrios C. Gklezakos, Vishwas Sathish
Predictive coding has emerged as a prominent model of how the brain learns through predictions, anticipating the importance accorded to predictive learning in recent AI architectur…
Hyper-Universal Policy Approximation: Learning to Generate Actions from a Single Image using Hypernets
Dimitrios C. Gklezakos, Rishi Jha, Rajesh P. N. Rao
Inspired by Gibson's notion of object affordances in human vision, we ask the question: how can an agent learn to predict an entire action policy for a novel object or environment…
Active Predictive Coding Networks: A Neural Solution to the Problem of Learning Reference Frames and Part-Whole Hierarchies
Dimitrios C. Gklezakos, Rajesh P. N. Rao
We introduce Active Predictive Coding Networks (APCNs), a new class of neural networks that solve a major problem posed by Hinton and others in the fields of artificial intelligenc…
Transformational Sparse Coding
Dimitrios C. Gklezakos, Rajesh P. N. Rao
A fundamental problem faced by object recognition systems is that objects and their features can appear in different locations, scales and orientations. Current deep learning metho…