Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Khalid, Irtaza"'
Autor:
Khalid, Irtaza, Schockaert, Steven
Developing models that can learn to reason is a notoriously challenging problem. We focus on reasoning in relational domains, where the use of Graph Neural Networks (GNNs) seems like a natural choice. However, previous work on reasoning with GNNs has
Externí odkaz:
http://arxiv.org/abs/2407.17396
Autor:
Khalid, Irtaza, Weidner, Carrie A., Jonckheere, Edmond A., Shermer, Sophie G., Langbein, Frank C.
Publikováno v:
Phys. Rev. Research 5, 043002 (2023)
We propose a model-based reinforcement learning (RL) approach for noisy time-dependent gate optimization with improved sample complexity over model-free RL. Sample complexity is the number of controller interactions with the physical system. Leveragi
Externí odkaz:
http://arxiv.org/abs/2304.09718
Autor:
Khalid, Irtaza, Weidner, Carrie A., Jonckheere, Edmond A., Shermer, Sophie G., Langbein, Frank C.
Publikováno v:
Phys Rev A. 107.032606 (2023)
Robustness of quantum operations or controls is important to build reliable quantum devices. The robustness-infidelity measure (RIM$_p$) is introduced to statistically quantify the robustness and fidelity of a controller as the p-order Wasserstein di
Externí odkaz:
http://arxiv.org/abs/2207.07801
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.