most citedDeep Autoencoders for Unsupervised Anomaly Detection in Wildfire Prediction

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

astro-ph.IM2025

Stereovision Image Processing for Planetary Navigation Maps with Semi-Global Matching and Superpixel Segmentation

Yan-Shan Lu, Miguel Arana-Catania, Saurabh Upadhyay +1

Mars exploration requires precise and reliable terrain models to ensure safe rover navigation across its unpredictable and often hazardous landscapes. Stereoscopic vision serves a…

cs.RO2025

Parameter Estimation using Reinforcement Learning Causal Curiosity: Limits and Challenges

Miguel Arana-Catania, Weisi Guo

Causal understanding is important in many disciplines of science and engineering, where we seek to understand how different factors in the system causally affect an experiment or s…

eess.SY2025

A causal learning approach to in-orbit inertial parameter estimation for multi-payload deployers

Konstantinos Platanitis, Miguel Arana-Catania, Saurabh Upadhyay +1

This paper discusses an approach to inertial parameter estimation for the case of cargo carrying spacecraft that is based on causal learning, i.e. learning from the responses of th…

cs.LG20241 cited

Deep Autoencoders for Unsupervised Anomaly Detection in Wildfire Prediction

İrem Üstek, Miguel Arana-Catania, Alexander Farr +1

Wildfires pose a significantly increasing hazard to global ecosystems due to the climate crisis. Due to its complex nature, there is an urgent need for innovative approaches to wil…

cs.RO2024

Causal Reinforcement Learning for Optimisation of Robot Dynamics in Unknown Environments

Julian Gerald Dcruz, Sam Mahoney, Jia Yun Chua +4

Autonomous operations of robots in unknown environments are challenging due to the lack of knowledge of the dynamics of the interactions, such as the objects' movability. This work…