43 citations · 54 across the 7 of their papers we have counts for
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cs.GT2020★ 6 cited
Learning Game-Theoretic Models of Multiagent Trajectories Using Implicit Layers
Philipp Geiger, Christoph-Nikolas Straehle
For prediction of interacting agents' trajectories, we propose an end-to-end trainable architecture that hybridizes neural nets with game-theoretic reasoning, has interpretable int…
cs.AI2020★ 2 cited
Causal Transfer for Imitation Learning and Decision Making under Sensor-shift
Jalal Etesami, Philipp Geiger
Learning from demonstrations (LfD) is an efficient paradigm to train AI agents. But major issues arise when there are differences between (a) the demonstrator's own sensory input,…