Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Saurabh Malani"'
Autor:
William Benman, Saachi Datta, David Gonzalez-Martinez, Gloria Lee, Juliette Hooper, Grace Qian, Gabrielle Leavitt, Lana Salloum, Gabrielle Ho, Sharvari Mhatre, Michael S. Magaraci, Michael Patterson, Sevile G. Mannickarottu, Saurabh Malani, Jose L. Avalos, Brian Y. Chow, Lukasz J. Bugaj
Publikováno v:
Communications Biology, Vol 6, Iss 1, Pp 1-14 (2023)
Abstract The ability to perform sophisticated, high-throughput optogenetic experiments has been greatly enhanced by recent open-source illumination devices that allow independent programming of light patterns in single wells of microwell plates. Howe
Externí odkaz:
https://doaj.org/article/3efa70a4a8c0485dbec94aa00969e823
Autor:
Saachi Datta, William Benman, David Gonzalez-Martinez, Gloria Lee, Juliette Hooper, Grace Qian, Gabrielle Leavitt, Lana Salloum, Gabrielle Ho, Sharvari Mhatre, Michael S. Magaraci, Michael Patterson, Sevile G. Mannickarottu, Saurabh Malani, Jose L. Avalos, Brian Y. Chow, Lukasz J. Bugaj
The ability to perform sophisticated, high-throughput optogenetic experiments has been greatly enhanced by recent open-source illumination devices that allow independent programming of light patterns in single wells of microwell plates. However, ther
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::258f4b0b97e930efc6a21365e2e1651d
https://doi.org/10.1101/2022.07.13.499906
https://doi.org/10.1101/2022.07.13.499906
Autor:
Gurudayal Gurudayal, Saurabh Malani, Joel W. Ager, Sophia Haussener, David Perone, Yanwei Lum
Publikováno v:
ACS Applied Energy Materials, vol 2, iss 6
Cascade catalytic processes perform multistep chemical transformations without isolating the intermediates. Here, we demonstrate a sequential cascade pathway to convert CO2 to C2+ hydrocarbons and oxygenates in a two-step electrocatalytic process usi
Autor:
Saurabh Malani, Ioannis G. Kevrekidis, Tianqi Cui, Felix P. Kemeth, Nikolaos Evangelou, Tom Bertalan
Publikováno v:
Chaos: An Interdisciplinary Journal of Nonlinear Science. 31:093111
We present an approach, based on learning an intrinsic data manifold, for the initialization of the internal state values of long short-term memory (LSTM) recurrent neural networks, ensuring consistency with the initial observed input data. Exploitin