23 citations · 66 across the 4 of their papers we have counts for
4 papers
Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting
Abdulmajid Murad, Frank Alexander Kraemer, Kerstin Bach +1
Data-driven forecasts of air quality have recently achieved more accurate short-term predictions. Despite their success, most of the current data-driven solutions lack proper quant…
Learning Task Agnostic Skills with Data-driven Guidance
Even Klemsdal, Sverre Herland, Abdulmajid Murad
To increase autonomy in reinforcement learning, agents need to learn useful behaviours without reliance on manually designed reward functions. To that end, skill discovery methods…
Information-Driven Adaptive Sensing Based on Deep Reinforcement Learning
Abdulmajid Murad, Frank Alexander Kraemer, Kerstin Bach +1
In order to make better use of deep reinforcement learning in the creation of sensing policies for resource-constrained IoT devices, we present and study a novel reward function ba…
Autonomous Management of Energy-Harvesting IoT Nodes Using Deep Reinforcement Learning
Abdulmajid Murad, Frank Alexander Kraemer, Kerstin Bach +1
Reinforcement learning (RL) is capable of managing wireless, energy-harvesting IoT nodes by solving the problem of autonomous management in non-stationary, resource-constrained set…