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pro vyhledávání: '"King, Daniel"'
Monitoring of Diffuse Intrinsic Pontine Glioma (DIPG) and Diffuse Midline Glioma (DMG) brain tumors in pediatric patients is key for assessment of treatment response. Response Assessment in Pediatric Neuro-Oncology (RAPNO) guidelines recommend the vo
Externí odkaz:
http://arxiv.org/abs/2410.14020
Autor:
King, Daniel J., Wood, Amanda G.
Publikováno v:
Network Neuroscience, Vol 4, Iss 1, Pp 274-291 (2020)
Morphometric similarity networks (MSNs) estimate organization of the cortex as a biologically meaningful set of similarities between anatomical features at the macro- and microstructural level, derived from multiple structural MRI (sMRI) sequences. T
Externí odkaz:
https://doaj.org/article/054ec273c7ec46918aa80fa91ad2e034
Autor:
Biderman, Dan, Portes, Jacob, Ortiz, Jose Javier Gonzalez, Paul, Mansheej, Greengard, Philip, Jennings, Connor, King, Daniel, Havens, Sam, Chiley, Vitaliy, Frankle, Jonathan, Blakeney, Cody, Cunningham, John P.
Low-Rank Adaptation (LoRA) is a widely-used parameter-efficient finetuning method for large language models. LoRA saves memory by training only low rank perturbations to selected weight matrices. In this work, we compare the performance of LoRA and f
Externí odkaz:
http://arxiv.org/abs/2405.09673
The localized active space self consistent field (LASSCF) method factorizes a complete active space (CAS) wave function into an antisymmetrized product of localized active space wave function fragments. Correlation between fragments is then reintrodu
Externí odkaz:
http://arxiv.org/abs/2403.15495
Autor:
Portes, Jacob, Trott, Alex, Havens, Sam, King, Daniel, Venigalla, Abhinav, Nadeem, Moin, Sardana, Nikhil, Khudia, Daya, Frankle, Jonathan
Publikováno v:
NeurIPS 2023
Although BERT-style encoder models are heavily used in NLP research, many researchers do not pretrain their own BERTs from scratch due to the high cost of training. In the past half-decade since BERT first rose to prominence, many advances have been
Externí odkaz:
http://arxiv.org/abs/2312.17482
Autor:
Miyabe, Shungo, Quanz, Brian, Shimada, Noriaki, Mitra, Abhijit, Yamamoto, Takahiro, Rastunkov, Vladimir, Alevras, Dimitris, Metcalf, Mekena, King, Daniel J. M., Mamouei, Mohammad, Jackson, Matthew D., Brown, Martin, Intallura, Philip, Park, Jae-Eun
Financial services is a prospect industry where unlocked near-term quantum utility could yield profitable potential, and, in particular, quantum machine learning algorithms could potentially benefit businesses by improving the quality of predictive m
Externí odkaz:
http://arxiv.org/abs/2312.00260