Zobrazeno 1 - 10
of 10 972
pro vyhledávání: '"A. Maddison"'
The reduced sensitivity of mean Southern Ocean zonal transport with respect to surface wind stress magnitude changes, known as eddy saturation, is studied in an idealised analytical model. The model is based on the assumption of a balance between sur
Externí odkaz:
http://arxiv.org/abs/2409.18035
Autor:
Cheng, Xingrui, Thurn, Andreas, Chen, Guangzhao, Jones, Gareth S., Coke, Maddison, Adshead, Mason, Michaels, Cathryn P., Balci, Osman, Ferrari, Andrea C., Atatüre, Mete, Curry, Richard, Smith, Jason M., Salter, Patrick S., Gangloff, Dorian A.
Spin-photon interfaces based on group-IV colour centres in diamond offer a promising platform for quantum networks. A key challenge in the field is realizing precise single-defect positioning and activation, which is crucial for scalable device fabri
Externí odkaz:
http://arxiv.org/abs/2409.07421
An automated framework is presented for the numerical solution of optimal control problems with PDEs as constraints, in both the stationary and instationary settings. The associated code can solve both linear and non-linear problems, and examples for
Externí odkaz:
http://arxiv.org/abs/2408.17312
Autor:
Islam, Sheikh Mohammed Shariful, Abrar, Moloud, Tegegne, Teketo, Loranjo, Liliana, Karmakar, Chandan, Awal, Md Abdul, Hossain, Md. Shahadat, Kabir, Muhammad Ashad, Mahmud, Mufti, Khosravi, Abbas, Siopis, George, Moses, Jeban C, Maddison, Ralph
Machine learning models have the potential to identify cardiovascular diseases (CVDs) early and accurately in primary healthcare settings, which is crucial for delivering timely treatment and management. Although population-based CVD risk models have
Externí odkaz:
http://arxiv.org/abs/2407.16721
Knowing the effect of an intervention is critical for human decision-making, but current approaches for causal effect estimation rely on manual data collection and structuring, regardless of the causal assumptions. This increases both the cost and ti
Externí odkaz:
http://arxiv.org/abs/2407.07018
Autor:
Dong, Honghua, Su, Qidong, Gao, Yubo, Li, Zhaoyu, Ruan, Yangjun, Pekhimenko, Gennady, Maddison, Chris J., Si, Xujie
Large Language Models (LLMs) have become increasingly capable of handling diverse tasks with the aid of well-crafted prompts and integration of external tools, but as task complexity rises, the workflow involving LLMs can be complicated and thus chal
Externí odkaz:
http://arxiv.org/abs/2406.13161
We study the problem of designing minimax procedures in linear regression under the quantile risk. We start by considering the realizable setting with independent Gaussian noise, where for any given noise level and distribution of inputs, we obtain t
Externí odkaz:
http://arxiv.org/abs/2406.12145
Autor:
Cotta, Leonardo, Maddison, Chris J.
Frontier Large Language Models (LLMs) can be socially discriminatory or sensitive to spurious features of their inputs. Because only well-resourced corporations can train frontier LLMs, we need robust test-time strategies to control such biases. Exis
Externí odkaz:
http://arxiv.org/abs/2406.07685
Autor:
Thudi, Anvith, Maddison, Chris J.
Training on mixtures of data distributions is now common in many modern machine learning pipelines, useful for performing well on several downstream tasks. Group distributionally robust optimization (group DRO) is one popular way to learn mixture wei
Externí odkaz:
http://arxiv.org/abs/2406.01477
Understanding how language model performance varies with scale is critical to benchmark and algorithm development. Scaling laws are one approach to building this understanding, but the requirement of training models across many different scales has l
Externí odkaz:
http://arxiv.org/abs/2405.10938