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The deployment of safe and trustworthy machine learning systems, and particularly complex black box neural networks, in real-world applications requires reliable and certified guarantees on their performance. The conformal prediction…
Food recognition and nutritional apps are trending technologies that may revolutionise the way people with diabetes manage their diet. Such apps can monitor food intake as a digital diary and even employ artificial intelligence to assess…
A novel forecast linear augmented projection (FLAP) method is introduced, which reduces the forecast error variance of any unbiased multivariate forecast without introducing bias. The method first constructs new component series which are…
In observational studies, the recorded treatment assignment is not purely random, but it is influenced by external factors such as patient characteristics, reimbursement policies, and existing guidelines. Therefore, the treatment effect can…
This paper reviews the state of the art in satellite and machine learning based poverty estimates and finds some interesting results. The most important factors correlated to the predictive power of welfare in the reviewed studies are the…
Mechatronic systems have increasingly high performance requirements for motion control. The low-frequency contribution of the flexible dynamics, i.e. the compliance, should be compensated for by means of snap feedforward to achieve high…
We revisit a classic "chicken-and-egg" problem in reinforcement learning: to safely improve a policy, the value function must be accurate on the state-visitation distribution of the updated policy. That distribution over states is unknown…
In the agricultural sector, the COVID-19 threatens to lead to a severe food security crisis in the region, with disruptions in the food supply chain and agricultural production expected to contract between 2.6% and 7%. From the food crop…
Snapchat, like many other social platforms, provides mechanisms for its users to report content and private/public interactions that violate their sense of safety and decency. From our experience and common sense, we can safely assume that…
Fake news is fabricated information that is presented as genuine, with intention to deceive the reader. Recently, the magnitude of people relying on social media for news consumption has increased significantly. Owing to this rapid…
Conformal prediction (CP) is a wrapper around traditional machine learning models, giving coverage guarantees under the sole assumption of exchangeability; in classification problems, for a chosen significance level $\varepsilon$, CP…
Propensity score (PS) methods are widely used to estimate treatment effects in non-randomized studies. Variance is typically estimated using sandwich or bootstrap methods, which can either treat the PS as estimated or fixed. The latter is…
We benchmark a multi-dimensional child nutrition intervention against an unconditional cash transfer of equal cost. Randomized variation in transfer amounts allows us to estimate impacts of cash transfers at expenditure levels equivalent to…
We perform a direct comparison of two state-of-the art single stellar population (SSP) models that have been used to demonstrate the non-universality of the low-mass end of the Initial Mass Function (IMF) slope. The two public versions of…
The OpenSSF Scorecard project is an automated tool to monitor the security health of open-source software. This study evaluates the applicability of the Scorecard tool and compares the security practices and gaps in the npm and PyPI…
New methods for modeling least-cost diets that meet nutritional requirements for health have emerged as important tools for informing nutrition policy and programming around the world. This study develops a three-step approach using cost of…
Spiking neural networks (SNNs) have gained attention as a promising alternative to traditional artificial neural networks (ANNs) due to their potential for energy efficiency and their ability to model spiking behavior in biological systems.…
Choice consistency with utility maximization, as a key assumption in economics, has been extensively used to evaluate decision quality of individuals and to predict real-world outcomes across different contexts. Here we investigate the…
Background: Transitions towards healthier, more environmentally sustainable diets would require large shifts in consumption patterns. Cost and affordability can be barriers to consuming healthy, sustainable diets. Objective: This study…
In this paper we study the simultaneous problems of food waste and hunger in the context of the possible solution of food (waste) rescue and redistribution. To this end, we develop an empirical model that can be used in Monte Carlo…