367 citations · 635 across the 9 of their papers we have counts for
11 papers
SurgTransfer: Multi-Step Latent Action Modeling for Action Transfer in Surgical World Model
Saurabh Koju, Love Panta, Deepak Thapa +6
Surgical world models have the potential to provide intra-operative guidance, accelerate risk-free training and facilitate transfer of expert surgical maneuvers. However, the use o…
Surgical Vision World Model
Saurabh Koju, Saurav Bastola, Prashant Shrestha +4
Realistic and interactive surgical simulation has the potential to facilitate crucial applications, such as medical professional training and autonomous surgical agent training. In…
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…
A Stochastic Bundle Method for Interpolating Networks
Alasdair Paren, Leonard Berrada, Rudra P. K. Poudel +1
We propose a novel method for training deep neural networks that are capable of interpolation, that is, driving the empirical loss to zero. At each iteration, our method constructs…
Embodied Visual Navigation with Automatic Curriculum Learning in Real Environments
Steven D. Morad, Roberto Mecca, Rudra P. K. Poudel +2
We present NavACL, a method of automatic curriculum learning tailored to the navigation task. NavACL is simple to train and efficiently selects relevant tasks using geometric featu…
Fast-SCNN: Fast Semantic Segmentation Network
Rudra P K Poudel, Stephan Liwicki, Roberto Cipolla
The encoder-decoder framework is state-of-the-art for offline semantic image segmentation. Since the rise in autonomous systems, real-time computation is increasingly desirable. In…
ContextNet: Exploring Context and Detail for Semantic Segmentation in Real-time
Rudra P K Poudel, Ujwal Bonde, Stephan Liwicki +1
Modern deep learning architectures produce highly accurate results on many challenging semantic segmentation datasets. State-of-the-art methods are, however, not directly transfera…
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker
James H Cole, Rudra PK Poudel, Dimosthenis Tsagkrasoulis +4
Machine learning analysis of neuroimaging data can accurately predict chronological age in healthy people and deviations from healthy brain ageing have been associated with cogniti…
Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation
Rudra P K Poudel, Pablo Lamata, Giovanni Montana
In cardiac magnetic resonance imaging, fully-automatic segmentation of the heart enables precise structural and functional measurements to be taken, e.g. from short-axis MR images…