58 citations · 237 across the 23 of their papers we have counts for
4 papers · 1 filter
Navigation under uncertainty: Trajectory prediction and occlusion reasoning with switching dynamical systems
Ran Wei, Joseph Lee, Shohei Wakayama +10
Predicting future trajectories of nearby objects, especially under occlusion, is a crucial task in autonomous driving and safe robot navigation. Prior works typically neglect to ma…
Variational Bayes Gaussian Splatting
Toon Van de Maele, Ozan Catal, Alexander Tschantz +2
Recently, 3D Gaussian Splatting has emerged as a promising approach for modeling 3D scenes using mixtures of Gaussians. The predominant optimization method for these models relies…
Gradient-free variational learning with conditional mixture networks
Conor Heins, Hao Wu, Dimitrije Markovic +3
Balancing computational efficiency with robust predictive performance is crucial in supervised learning, especially for critical applications. Standard deep learning models, while…
From pixels to planning: scale-free active inference
Karl Friston, Conor Heins, Tim Verbelen +7
This paper describes a discrete state-space model -- and accompanying methods -- for generative modelling. This model generalises partially observed Markov decision processes to in…