626 citations · 1.2k across the 12 of their papers we have counts for
Showing 2015Show all
2 papers · 1 filter
cs.LG2015★ 284 cited
Maximum Entropy Deep Inverse Reinforcement Learning
Markus Wulfmeier, Peter Ondruska, Ingmar Posner
This paper presents a general framework for exploiting the representational capacity of neural networks to approximate complex, nonlinear reward functions in the context of solving…
cs.CL2015★ 626 cited
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing
Ankit Kumar, Ozan Irsoy, Peter Ondruska +6
Most tasks in natural language processing can be cast into question answering (QA) problems over language input. We introduce the dynamic memory network (DMN), a neural network arc…