147 citations · 639 across the 19 of their papers we have counts for
4 papers · 1 filter
Physics guided neural networks for modelling of non-linear dynamics
Haakon Robinson, Suraj Pawar, Adil Rasheed +1
The success of the current wave of artificial intelligence can be partly attributed to deep neural networks, which have proven to be very effective in learning complex patterns fro…
Physics guided machine learning using simplified theories
Suraj Pawar, Omer San, Burak Aksoylu +2
Recent applications of machine learning, in particular deep learning, motivate the need to address the generalizability of the statistical inference approaches in physical sciences…
Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning
Eivind Meyer, Haakon Robinson, Adil Rasheed +1
In this article, we explore the feasibility of applying proximal policy optimization, a state-of-the-art deep reinforcement learning algorithm for continuous control tasks, on the…
Dissecting Deep Neural Networks
Haakon Robinson, Adil Rasheed, Omer San
In exchange for large quantities of data and processing power, deep neural networks have yielded models that provide state of the art predication capabilities in many fields. Howev…