The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …

Computational methods in fluid research have been progressing during the past few years,
driven by the incorporation of massive amounts of data, either in textual or graphical form …

We design a predictive layer for structured-output prediction (SOP) that can be plugged into
any neural network guaranteeing its predictions are consistent with a set of predefined …

SHAP explanations are a popular feature-attribution mechanism for explainable AI. They
use game-theoretic notions to measure the influence of individual features on the prediction …

Probabilistic models are at the very core of modern machine learning (ML) and artificial
intelligence (AI). Indeed, probability theory provides a principled and almost universally …

Circuit representations are becoming the lingua franca to express and reason about
tractable generative and discriminative models. In this paper, we show how complex …

Recently, carbon capture has gained increased attention as a sustainable way for mitigating
global warming. One of the promising technologies for carbon capture is the adsorption …

The COVID-19 pandemic has presented an unprecedented challenge to the healthcare
system. Identifying the genomics and clinical biomarkers for effective patient stratification …

Juice is an open-source Julia package providing tools for logic and probabilistic reasoning
and learning based on logic circuits (LCs) and probabilistic circuits (PCs). It provides a …

Understanding the behavior of learned classifiers is an important task, and various black-
box explanations, logical reasoning approaches, and model-specific methods have been …