Excited to share our team's research on the MET receptor's role in Acetaminophen-induced liver injury at The Liver Meeting, AASLD in Boston today at 1 PM at level-1 Hall A- poster 4315. Looking forward to meaningful engagement with the fellow attendees. #aasld#TLM2023#PLRC
I am happy to present our team's work on the role of EGFR in drug induced liver injury at the University of Pittsburgh, Pittsburgh Liver Research Center retreat tomorrow at 5.00 PM. Looking forward to interact with the attendees. @PLRC_PittLiver#plrc#pittsburgh
@rpokolkata@ashishmiddha84
I sent my NORI documents by FedEx on July 29. I got an email from RPO on Sept 15 that the police verification is pending. However the local police have informed my family members that they have not got anything.
Can you please let me know the status?
@argonne_lcf Thanks a lot for this amazing two-week training project! I was so happy to be here, and I have definitely learned a lot of HPC techniques! Most importantly, I've met some wonderful people here! I feel very fortunate to have met you! @sgoswami26@itshelenxu
The 2022 @argonne Training Program on Extreme-Scale Computing comes to a close today. With its 10th year now in the books, nearly 700 participants have attended ATPESC to learn how to use the world's most powerful supercomputers for scientific research.
https://t.co/y47KzNASTz
ATPESC is underway! Celebrating its 10th anniversary, the two-week training course provides researchers the opportunity to learn the latest supercomputing tools and techniques from some of the world's leading #HPC experts.
https://t.co/m3JAutnjLM gave my husband and me a nightmare experience. I can now plainly discern a state of deterrence and deliberate harassment of travelers.
Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms
https://t.co/lc9C7xO88d
by @sgoswami26 et al.
#ComputerScience#Learning
Have you quantified over-parameterization in surrogate models?
https://t.co/8Axu34h7Ld
@kontolati and I have presented a detailed quantification of the effect of over-parametrization in manifold-based surrogates and deep operator networks.
Which surrogate model will give more accuracy when you have less training data than when you have a large training dataset? https://t.co/8Axu34h7Ld
@kontolati and I have demonstrated the effect of training dataset size on the generalization accuracy of #mPCE, #DeepONet, and #FNO