Zobrazeno 1 - 10
of 13 643
pro vyhledávání: '"A. Mcinerney"'
Autor:
Feng, Yanxin, Wu, Andrew, McInerney, James, Sarkar, Siddhartha, Mao, Xiaoming, Rocklin, D. Zeb
Origami principles are used to create strong, lightweight structures with complex mechanical response. However, identifying the fundamental physical principles that determine a sheet's behavior remains a challenge. We introduce a new analytic theory
Externí odkaz:
http://arxiv.org/abs/2410.02174
Conformal Prediction methods have finite-sample distribution-free marginal coverage guarantees. However, they generally do not offer conditional coverage guarantees, which can be important for high-stakes decisions. In this paper, we propose a novel
Externí odkaz:
http://arxiv.org/abs/2409.17466
Publikováno v:
European Psychiatry, Vol 65, Pp S288-S288 (2022)
Introduction People with diabetes are vulnerable to diabetes-related distress and are more likely to experience depressive and anxiety symptoms than the general population. Diabetes distress, depressive, and anxiety symptoms also tend to commonly co-
Externí odkaz:
https://doaj.org/article/3b1cc5e1840f4d45bcbe4637e118bd6a
Autor:
Arroyo, Alberto Mario Ceballos, Munnangi, Monica, Sun, Jiuding, Zhang, Karen Y. C., McInerney, Denis Jered, Wallace, Byron C., Amir, Silvio
Instruction-tuned Large Language Models (LLMs) can perform a wide range of tasks given natural language instructions to do so, but they are sensitive to how such instructions are phrased. This issue is especially concerning in healthcare, as clinicia
Externí odkaz:
http://arxiv.org/abs/2407.09429
Autor:
McInerney, James, Kallus, Nathan
The Laplace approximation (LA) of the Bayesian posterior is a Gaussian distribution centered at the maximum a posteriori estimate. Its appeal in Bayesian deep learning stems from the ability to quantify uncertainty post-hoc (i.e., after standard netw
Externí odkaz:
http://arxiv.org/abs/2403.10671
Autor:
Ayoub, Alex, Wang, Kaiwen, Liu, Vincent, Robertson, Samuel, McInerney, James, Liang, Dawen, Kallus, Nathan, Szepesvári, Csaba
We propose training fitted Q-iteration with log-loss (FQI-log) for batch reinforcement learning (RL). We show that the number of samples needed to learn a near-optimal policy with FQI-log scales with the accumulated cost of the optimal policy, which
Externí odkaz:
http://arxiv.org/abs/2403.05385
Autor:
McInerney, Denis Jered, Dickinson, William, Flynn, Lucy C., Young, Andrea C., Young, Geoffrey S., van de Meent, Jan-Willem, Wallace, Byron C.
Many diagnostic errors occur because clinicians cannot easily access relevant information in patient Electronic Health Records (EHRs). In this work we propose a method to use LLMs to identify pieces of evidence in patient EHR data that indicate incre
Externí odkaz:
http://arxiv.org/abs/2402.10109
Origami metamaterial design enables drastic qualitative changes in the response properties of a thin sheet via the addition of a repeating pattern of folds based around a rigid folding motion. Known also as a mechanism, this folding motion will have
Externí odkaz:
http://arxiv.org/abs/2312.12432
Autor:
Zhang, Gongbo, Jin, Qiao, McInerney, Denis Jered, Chen, Yong, Wang, Fei, Cole, Curtis L., Yang, Qian, Wang, Yanshan, Malin, Bradley A., Peleg, Mor, Wallace, Byron C., Lu, Zhiyong, Weng, Chunhua, Peng, Yifan
Evidence-based medicine promises to improve the quality of healthcare by empowering medical decisions and practices with the best available evidence. The rapid growth of medical evidence, which can be obtained from various sources, poses a challenge
Externí odkaz:
http://arxiv.org/abs/2311.11211
Autor:
McInerney, Andrew, Burke, Kevin
Feedforward neural networks (FNNs) are typically viewed as pure prediction algorithms, and their strong predictive performance has led to their use in many machine-learning applications. However, their flexibility comes with an interpretability trade
Externí odkaz:
http://arxiv.org/abs/2311.08139