29 citations · 31 across the 6 of their papers we have counts for
4 papers · 1 filter
ReCoRe: Regularized Contrastive Representation Learning of World Model
Rudra P. K. Poudel, Harit Pandya, Stephan Liwicki +1
While recent model-free Reinforcement Learning (RL) methods have demonstrated human-level effectiveness in gaming environments, their success in everyday tasks like visual navigati…
LanGWM: Language Grounded World Model
Rudra P. K. Poudel, Harit Pandya, Chao Zhang +1
Recent advances in deep reinforcement learning have showcased its potential in tackling complex tasks. However, experiments on visual control tasks have revealed that state-of-the-…
Contrastive Unsupervised Learning of World Model with Invariant Causal Features
Rudra P. K. Poudel, Harit Pandya, Roberto Cipolla
In this paper we present a world model, which learns causal features using the invariance principle. In particular, we use contrastive unsupervised learning to learn the invariant…
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces
Philipp Becker, Harit Pandya, Gregor Gebhardt +3
In order to integrate uncertainty estimates into deep time-series modelling, Kalman Filters (KFs) (Kalman et al., 1960) have been integrated with deep learning models, however, suc…