Clemens Rosenbaum
TitleCited byYear
Routing networks: Adaptive selection of non-linear functions for multi-task learning
C Rosenbaum, T Klinger, M Riemer
arXiv preprint arXiv:1711.01239, 2017
422017
Eigenoption discovery through the deep successor representation
MC Machado, C Rosenbaum, X Guo, M Liu, G Tesauro, M Campbell
arXiv preprint arXiv:1710.11089, 2017
372017
Learning to query, reason, and answer questions on ambiguous texts
X Guo, T Klinger, C Rosenbaum, JP Bigus, M Campbell, B Kawas, ...
102016
Deep reinforcement learning with macro-actions
IP Durugkar, C Rosenbaum, S Dernbach, S Mahadevan
arXiv preprint arXiv:1606.04615, 2016
92016
Routing networks and the challenges of modular and compositional computation
C Rosenbaum, I Cases, M Riemer, T Klinger
arXiv preprint arXiv:1904.12774, 2019
72019
Recursive routing networks: Learning to compose modules for language understanding
I Cases, C Rosenbaum, M Riemer, A Geiger, T Klinger, A Tamkin, O Li, ...
Proceedings of the 2019 Conference of the North American Chapter of the …, 2019
42019
On the Role of Weight Sharing During Deep Option Learning
M Riemer, I Cases, C Rosenbaum, M Liu, G Tesauro
arXiv preprint arXiv:1912.13408, 2019
22019
DISPATCHED ROUTING NETWORKS
C Rosenbaum, I Cases, M Riemer, A Geiger, L Karttunen, JD Greene, ...
2019
e-QRAQ: A Multi-turn Reasoning Dataset and Simulator with Explanations
C Rosenbaum, T Gao, T Klinger
arXiv preprint arXiv:1708.01776, 2017
2017
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Articles 1–9