Search Results for author:
Found 5 papers, 2 papers with code
Real-World Robot Applications of Foundation Models: A Review
This paper provides an overview of the practical application of foundation models in real-world robotics, with a primary emphasis on the replacement of specific components within existing robot systems.
Detecting and Quantifying Malicious Activity with Simulation-based Inference
We propose the use of probabilistic programming techniques to tackle the malicious user identification problem in a recommendation algorithm.
Simulation-Based Inference for Global Health Decisions
The COVID-19 pandemic has highlighted the importance of in-silico epidemiological modelling in predicting the dynamics of infectious diseases to inform health policy and decision makers about suitable prevention and containment strategies.
Transflow Learning: Repurposing Flow Models Without Retraining
It is well known that deep generative models have a rich latent space, and that it is possible to smoothly manipulate their outputs by traversing this latent space.
Multitask Soft Option Learning
We present Multitask Soft Option Learning(MSOL), a hierarchical multitask framework based on Planning as Inference.
