activity
20202026
most citedModelling non-reinforced preferences using selective attention

2 citations · 2 across the 7 of their papers we have counts for

collaborators

8 papers

cs.RO2026

Less Language, More Latents: Annotation-Efficient VLAs for Driving

Alexey Zakharov, Kemal Oksuz, Puneet K. Dokania

Vision-language-action models (VLA) promise human-steerable autonomous driving, but their training is bottlenecked by the scarcity of frames paired with natural-language instructio…

cs.LG2023

Long-horizon video prediction using a dynamic latent hierarchy

Alexey Zakharov, Qinghai Guo, Zafeirios Fountas

The task of video prediction and generation is known to be notoriously difficult, with the research in this area largely limited to short-term predictions. Though plagued with nois…

cs.LG2022★ 2 cited

Modelling non-reinforced preferences using selective attention

Noor Sajid, Panagiotis Tigas, Zafeirios Fountas +3

How can artificial agents learn non-reinforced preferences to continuously adapt their behaviour to a changing environment? We decompose this question into two challenges: () en…

q-bio.NC2022

Bayesian sense of time in biological and artificial brains

Zafeirios Fountas, Alexey Zakharov

Enquiries concerning the underlying mechanisms and the emergent properties of a biological brain have a long history of theoretical postulates and experimental findings. Today, the…

cs.LG2021

Variational Predictive Routing with Nested Subjective Timescales

Alexey Zakharov, Qinghai Guo, Zafeirios Fountas

Discovery and learning of an underlying spatiotemporal hierarchy in sequential data is an important topic for machine learning. Despite this, little work has been done to explore h…

cs.LG2020

Episodic Memory for Learning Subjective-Timescale Models

Alexey Zakharov, Matthew Crosby, Zafeirios Fountas

In model-based learning, an agent's model is commonly defined over transitions between consecutive states of an environment even though planning often requires reasoning over multi…

cs.CV2020

Geometric Deep Learning for Post-Menstrual Age Prediction based on the Neonatal White Matter Cortical Surface

Vitalis Vosylius, Andy Wang, Cemlyn Waters +8

Accurate estimation of the age in neonates is essential for measuring neurodevelopmental, medical, and growth outcomes. In this paper, we propose a novel approach to predict the po…

eess.IV2020

Keypoints Localization for Joint Vertebra Detection and Fracture Severity Quantification

Maxim Pisov, Vladimir Kondratenko, Alexey Zakharov +4

Vertebral body compression fractures are reliable early signs of osteoporosis. Though these fractures are visible on Computed Tomography (CT) images, they are frequently missed by…