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Abstract: Estimating and searching source information such as the location and release rate, called a source term, have many applications across environmental, medical, and security domains. The ...

Abstract: High-dimensional time series appear in many scientific setups, demanding a nuanced approach to model and analyze the underlying dependence structure. Theoretical advancements so far often ...

This repository contains a simulation-based inference benchmark framework, sbibm, which we describe in the associated manuscript "Benchmarking Simulation-based Inference". A short summary of the paper ...

This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...

Perceptual judgments of ambiguous stimuli are often biased by prior expectations. These biases may offer a window into the neural computations that give rise to perceptual interpretations of the ...

PyVBMC is a Python implementation of the Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference, previously implemented in MATLAB. VBMC is an approximate inference method ...

Erdoğan's first visit to Iraq in 13 years led to 26 signed memorandums, including one for the Development Road Project. This project aims to create a trade corridor from Basra to Turkey and eventually ...

The United States and Mexico have grappled with increasing arms and drug trafficking for several years. In response to recent surges in violence, the Mexican Attorney General of the Republic (FGR) and ...

1 Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK 2 Department of Geography and Planning, University of Liverpool, Liverpool, UK Correspondence to: I Buchan ...

We revisit the problem of ensuring statistically valid inferences across diverse target populations from a single source of training data. Our approach builds a surprising technical connection between ...