Reliable uncertainty quantification (UQ) is essential in medical AI. Evidential Deep Learning (EDL) offers a computationally efficient way to quantify model uncertainty alongside predictions, unlike traditional methods such as Monte Carlo (MC) Dropou...
Recent studies in active learning, particularly in uncertainty sampling, have focused on the decomposition of model uncertainty into reducible and irreducible uncertainties. In this paper, the aim is to simplify the computational process while elimin...
# AUGUST 28th, 2025~Lynas Rare Earths Flags Texas Plant Uncertainty [Lynas Rare Earths Flags Texas Plant Uncertainty](https://www.msn.com/en-us/money/companies/lynas-rare-earths-flags-texas-plant-unc...
Uncertainty quantification is a fundamental yet unsolved problem for deep learning. The Bayesian framework provides a principled way of uncertainty estimation but is often not scalable to modern deep neural nets (DNNs) that have a large number of par...
There is a lot of uncertainty about of Bitcoin, so many turn to the altcoin market to diversity their crypto holdings, only to find more uncertainty. CoinMarketCap lists over 500 coins, and there are probably more. In this brief post, I offer Maxcoin’s qualifications as a worthy…
In Part II of this two-part paper, we analyze the marginal prices derived in Part I of this two-part paper within a robust optimization framework. The load and generation are priced at Locational Marginal Price (LMP) while the uncertainty and generat...
Neural networks are powerful tools in various applications, and quantifying their uncertainty is crucial for reliable decision-making. In the deep learning field, the uncertainties are usually categorized into aleatoric (data) and epistemic (model) u...
We present FORGE, a method for sim-to-real transfer of force-aware manipulation policies in the presence of significant pose uncertainty. During simulation-based policy learning, FORGE combines a force threshold mechanism with a dynamics randomizatio...
In order to estimate the uncertainty of the measuring process, one needs to consider the systematic and constant errors along with other factors that contribute to the uncertainty due to scatter of results …
In economics, Knightian uncertainty is a lack of any quantifiable knowledge about some possible occurrence, as opposed to the presence of quantifiable
The last few years has seen a growing debate about techniques for managing uncertainty in AI systems. Unfortunately this debate has been cast as a rivalry between AI methods and classical probability based ones. Three arguments for extending the prob...
IJCAI2020 & IJCV2021 :city_sunrise: Unsupervised Scene Adaptation with Memory Regularization in vivo (⭐ 396)
In mathematics, the uncertainty exponent is a method of measuring the fractal dimension of a basin boundary. In a chaotic scattering system, the invariant
Scheduling in the factory setting is compounded by computational complexity and temporal uncertainty. Together, these two factors guarantee that the process of constructing an optimal schedule will be costly and the chances of executing that schedule...
In metrology, measurement uncertainty is the expression of the statistical dispersion of the values attributed to a quantity measured on an interval or
I recently came across this really helpful tip in an article by Jon Herschfield. He basically says that accepting uncertainty does not mean accepting that there's a 50/50 chance your feared outcome is...
I do. At best I hate it and at worst it makes me extremely concerned. By uncertainty I mean like being uncertain of something and wishing you could know about something in advance before engaging with...
Fear, uncertainty, and doubt (FUD) is a manipulative propaganda tactic used in technology sales, marketing, public relations, politics, polling, and cults
Large Multimodal Models (LMMs), harnessing the complementarity among diverse modalities, are often considered more robust than pure Language Large Models (LLMs); yet do LMMs know what they do not know? There are three key open questions remaining: (1...
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