Contradictory uncertainty relations [PDF]
Phys. Rev. A 84, 034101 (2011), 2011 We show within a very simple framework that different measures of fluctuations lead to uncertainty relations resulting in contradictory conclusions. More specifically we focus on Tsallis and Renyi entropic uncertainty relations and we get that the minimum uncertainty states of some uncertainty relations are the maximum uncertainty states of closely ...
A. Renyi +3 more
arxiv +6 more sources
Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation [PDF]
International Conference on Learning Representations, 2023 We introduce a method to measure uncertainty in large language models. For tasks like question answering, it is essential to know when we can trust the natural language outputs of foundation models.
Lorenz Kuhn, Y. Gal, Sebastian Farquhar
semanticscholar +1 more source
Advancement of Project Management, Economics, and Social Effects and Risk Assessment in the Seventeenth ICMSEM Proceedings [PDF]
E3S Web of Conferences, 2023 Management Science and Engineering Management (MSEM) has significantly contributed to socio-economic development, especially management and control processes.
Xu Jiuping
doaj +1 more source
Teaching Models to Express Their Uncertainty in Words [PDF]
Trans. Mach. Learn. Res., 2022 We show that a GPT-3 model can learn to express uncertainty about its own answers in natural language -- without use of model logits. When given a question, the model generates both an answer and a level of confidence (e.g."90% confidence"or"high ...
Stephanie C. Lin +2 more
semanticscholar +1 more source
Advancement of Sustainable Development, Decision Support Systems, and Data Science Based on the Seventeenth ICMSEM Proceedings [PDF]
E3S Web of Conferences, 2023 Management science (MS) uses a variety of scientific researchbased principles and analytical methods, such as mathematical modeling and data analysis, to make decisions and solve complex problems, and has strong connections to management, data, economics,
Xu Jiuping
doaj +1 more source
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison [PDF]
AAAI Conference on Artificial Intelligence, 2019 Large, labeled datasets have driven deep learning methods to achieve expert-level performance on a variety of medical imaging tasks. We present CheXpert, a large dataset that contains 224,316 chest radiographs of 65,240 patients.
J. Irvin +19 more
semanticscholar +1 more source
Design of a Computable Approximate Reasoning Logic System for AI
Mathematics, 2022 The fuzzy logic reasoning based on the “If... then...” rule is not the inaccurate reasoning of AI against ambiguity because fuzzy reasoning is antilogical. In order to solve this problem, a redundancy theory for discriminative weight filtering containing
Kaidi Liu, Yancang Li, Rong Cui
doaj +1 more source
Multi-task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2017 Numerous deep learning applications benefit from multitask learning with multiple regression and classification objectives. In this paper we make the observation that the performance of such systems is strongly dependent on the relative weighting between
Alex Kendall, Y. Gal, R. Cipolla
semanticscholar +1 more source
Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information [PDF]
IEEE Transactions on Information Theory, 2004 This paper considers the model problem of reconstructing an object from incomplete frequency samples. Consider a discrete-time signal f/spl isin/C/sup N/ and a randomly chosen set of frequencies /spl Omega/.
E. Candès, J. Romberg, T. Tao
semanticscholar +1 more source
A survey of uncertainty in deep neural networks [PDF]
Artificial Intelligence Review, 2021 Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more and more important ...
J. Gawlikowski +13 more
semanticscholar +1 more source