209 citations · 712 across the 26 of their papers we have counts for
7 papers · 1 filter
Deep learning empowered sensor fusion boosts infant movement classification
Tomas Kulvicius, Dajie Zhang, Luise Poustka +8
To assess the integrity of the developing nervous system, the Prechtl general movement assessment (GMA) is recognized for its clinical value in diagnosing neurological impairments…
Combining Optimal Path Search With Task-Dependent Learning in a Neural Network
Tomas Kulvicius, Minija Tamosiunaite, Florentin Wörgötter
Finding optimal paths in connected graphs requires determining the smallest total cost for traveling along the graph's edges. This problem can be solved by several classical algori…
Reinforcement Learning
Olivier Buffet, Olivier Pietquin, Paul Weng
Reinforcement learning (RL) is a general framework for adaptive control, which has proven to be efficient in many domains, e.g., board games, video games or autonomous vehicles. In…
One-shot path planning for multi-agent systems using fully convolutional neural network
Tomas Kulvicius, Sebastian Herzog, Timo Lüddecke +2
Path planning plays a crucial role in robot action execution, since a path or a motion trajectory for a particular action has to be defined first before the action can be executed.…
Generation of Paths in a Maze using a Deep Network without Learning
Tomas Kulvicius, Sebastian Herzog, Minija Tamosiunaite +1
Trajectory- or path-planning is a fundamental issue in a wide variety of applications. Here we show that it is possible to solve path planning for multiple start- and end-points hi…
Attention on Abstract Visual Reasoning
Lukas Hahne, Timo Lüddecke, Florentin Wörgötter +1
Attention mechanisms have been boosting the performance of deep learning models on a wide range of applications, ranging from speech understanding to program induction. However, de…