q2b 2022 sv | a convergence theory for over-parameterized variational quantum eigensolvers | jpmc
Published 1 year ago • 74 plays • Length 17:23Download video MP4
Download video MP3
Similar videos
-
1:02:54
aqis '20: patrick coles, promises and challenges of variational quantum algorithms
-
20:16
q2b 2022 sv | geometric quantum machine learning | marco cerezo | los alamos national laboratory
-
20:52
q2b 2022 sv | the quantum value chain: competing within a crowded industry | doug finke | gqi
-
19:00
q2b 2022 sv | end-to-end solutions with neutral-atom quantum computing | alex keesling | quera
-
20:34
q2b 2022 sv | current status & prospects | shintaro sato | fujitsu limited
-
19:33
q2b 2022 sv | entangling the ecosystem: 5 diverse stories of quantum collaborations | mark wolf
-
17:07
q2b 2023 tokyo | addressing quantum computing control challenges | marc almendros
-
18:10
q2b 2022 sv | quantum computing beyond the circuit model | joe fitzsimons |horizon quantum computing
-
18:50
q2b 2022 sv | application specific quantum computing at bleximo | fabio sanches | bleximo
-
20:58
q2b 2022 sv | doubling the size of quantum simulators by entanglement forging | andrew eddins | ibm
-
22:27
q2b 2022 sv | aqt: a collaborative, multidisciplinary approach to enable tomorrow’s quist | lbnl
-
23:49
q2b 2022 sv | quantum algorithms research at afrl | daniel koch | afrl
-
12:15
q2b 2022 sv | australia; world-class quantum talent and gateway to apac | jessica richman
-
17:06
q2b 2022 sv | quantum: ahead of ready | dani couger | lockheed martin