161 citations · 528 across the 21 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…
A theory of generalised coordinates for stochastic differential equations
Lancelot Da Costa, Nathaël Da Costa, Conor Heins +5
Stochastic differential equations are ubiquitous modelling tools in physics and the sciences. In most modelling scenarios, random fluctuations driving dynamics or motion have some…
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…