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pro vyhledávání: '"Hartford A"'
In drug discovery, highly automated high-throughput laboratories are used to screen a large number of compounds in search of effective drugs. These experiments are expensive, so we might hope to reduce their cost by experimenting on a subset of the c
Externí odkaz:
http://arxiv.org/abs/2410.19631
Autor:
Zuheng, Xu, Jain, Moksh, Denton, Ali, Whitfield, Shawn, Didolkar, Aniket, Earnshaw, Berton, Hartford, Jason
Pairwise interactions between perturbations to a system can provide evidence for the causal dependencies of the underlying underlying mechanisms of a system. When observations are low dimensional, hand crafted measurements, detecting interactions amo
Externí odkaz:
http://arxiv.org/abs/2409.07594
Efficiently post-training large language models remains a challenging task due to the vast computational resources required. We present Spectrum, a method that accelerates LLM training by selectively targeting layer modules based on their signal-to-n
Externí odkaz:
http://arxiv.org/abs/2406.06623
Many causal systems such as biological processes in cells can only be observed indirectly via measurements, such as gene expression. Causal representation learning -- the task of correctly mapping low-level observations to latent causal variables --
Externí odkaz:
http://arxiv.org/abs/2405.20482
Scientific hypotheses typically concern specific aspects of complex, imperfectly understood or entirely unknown mechanisms, such as the effect of gene expression levels on phenotypes or how microbial communities influence environmental health. Such q
Externí odkaz:
http://arxiv.org/abs/2405.19985
Autor:
Xi, Johnny, Hartford, Jason
Multimodal representation learning techniques typically rely on paired samples to learn common representations, but paired samples are challenging to collect in fields such as biology where measurement devices often destroy the samples. This paper pr
Externí odkaz:
http://arxiv.org/abs/2404.01595
Autor:
Ward, Abbi, Li, Jimmy, Wang, Julie, Lakshminarasimhan, Sriram, Carrick, Ashley, Campana, Bilson, Hartford, Jay, S, Pradeep Kumar, Tiyasirichokchai, Tiya, Virmani, Sunny, Wong, Renee, Matias, Yossi, Corrado, Greg S., Webster, Dale R., Siegel, Dawn, Lin, Steven, Ko, Justin, Karthikesalingam, Alan, Semturs, Christopher, Rao, Pooja
Background: Health datasets from clinical sources do not reflect the breadth and diversity of disease in the real world, impacting research, medical education, and artificial intelligence (AI) tool development. Dermatology is a suitable area to devel
Externí odkaz:
http://arxiv.org/abs/2402.18545
Causal representation learning has showed a variety of settings in which we can disentangle latent variables with identifiability guarantees (up to some reasonable equivalence class). Common to all of these approaches is the assumption that (1) the l
Externí odkaz:
http://arxiv.org/abs/2310.19054
Quantification of the political leaning of online news articles can aid in understanding the dynamics of political ideology in social groups and measures to mitigating them. However, predicting the accurate political leaning of a news article with ma
Externí odkaz:
http://arxiv.org/abs/2309.05981
Publikováno v:
BMC Health Services Research, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background Intermediate care (IC) services bridge the transition for older patients from the hospital to the home. Despite the goal of involving individuals in their recovery process, these services often become standardised, leading to comm
Externí odkaz:
https://doaj.org/article/d0402a384aa3479caad7969dd99ce262
