Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Siddharth Goyal"'
Publikováno v:
2022 1st International Conference on Informatics (ICI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91d2a262e16e0653dc62f8f6b9c9777c
https://doi.org/10.1109/ici53355.2022.9786878
https://doi.org/10.1109/ici53355.2022.9786878
Autor:
Richard Tran, Janice Lan, Muhammed Shuaibi, Brandon M. Wood, Siddharth Goyal, Abhishek Das, Javier Heras-Domingo, Adeesh Kolluru, Ammar Rizvi, Nima Shoghi, Anuroop Sriram, Félix Therrien, Jehad Abed, Oleksandr Voznyy, Edward H. Sargent, Zachary Ulissi, C. Lawrence Zitnick
The development of machine learning models for electrocatalysts requires a broad set of training data to enable their use across a wide variety of materials. One class of materials that currently lacks sufficient training data is oxides, which are cr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6d071f29a5d51a9516c9a6213f3abc17
Publikováno v:
Building Services Engineering Research and Technology. 40:758-766
Advanced controls play an essential role toward the improvement of building operational efficiency and the integration of responsive loads in buildings for grid services. Ideally, control algorithms must be sufficiently tested and validated before th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e8bbd0cbf158c30379205f43790d48c
https://doi.org/10.1177/0143624419846775
https://doi.org/10.1177/0143624419846775
Autor:
Adeesh Kolluru, Nima Shoghi, Muhammed Shuaibi, Siddharth Goyal, Abhishek Das, C. Lawrence Zitnick, Zachary Ulissi
Publikováno v:
The Journal of Chemical Physics. 156:184702
Recent advances in Graph Neural Networks (GNNs) have transformed the space of molecular and catalyst discovery. Despite the fact that the underlying physics across these domains remain the same, most prior work has focused on building domain-specific
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::acc574d18cf6a84e96d33337a9c84a5d
https://doi.org/10.1063/5.0088019
https://doi.org/10.1063/5.0088019
Autor:
Brandon Wood, Lowik Chanussot, Weihua Hu, Zachary W. Ulissi, Muhammed Shuaibi, Siddharth Goyal, Devi Parikh, Morgane Riviere, Thibaut Lavril, Anuroop Sriram, C. Lawrence Zitnick, Kevin Tran, Aini Palizhati, Javier Heras-Domingo, Junwoong Yoon, Caleb Ho, Abhishek Das
Catalyst discovery and optimization is key to solving many societal and energy challenges including solar fuels synthesis, long-term energy storage, and renewable fertilizer production. Despite considerable effort by the catalysis community to apply
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea5ff843439f29f4796da51e2972b109
http://arxiv.org/abs/2010.09990
http://arxiv.org/abs/2010.09990
Autor:
Siddharth Goyal
This book focuses primarily on both technical and business aspects needed to select, design, develop and deploy control application (or product) successfully for multiple components in building systems. Designing and deploying a control application r
Publikováno v:
Journal of the American Chemical Society. 139:14931-14946
A delicate balance of different types of intramolecular interactions makes the folded states of proteins marginally more stable than the unfolded states. Experiments use thermal, chemical, or mechanical stress to perturb the folding equilibrium for e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a6272a350066563ea319710c2196357f
https://doi.org/10.1021/jacs.7b05463
https://doi.org/10.1021/jacs.7b05463
Publikováno v:
2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE).
Gearless wind energy conversion system based supplies can be a long term solution in case of distributed generation. This paper validates a modified control algorithm for maximum power point tracking of Permanent magnet synchronous generator (PMSG) b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::868cf9d0d900f4561f4293c30502c01b
https://doi.org/10.1109/rdcape47089.2019.8979101
https://doi.org/10.1109/rdcape47089.2019.8979101
Autor:
Demi Guo, Siddharth Goyal, Jason Liu, Alexander Rives, Joshua Meier, Tom Sercu, Zeming Lin, Rob Fergus, C. Lawrence Zitnick, Jerry Ma, Myle Ott
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America
Significance Learning biological properties from sequence data is a logical step toward generative and predictive artificial intelligence for biology. Here, we propose scaling a deep contextual language model with unsupervised learning to sequences s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a3730278797e814b021e2d2a64c2ab3