Abstract: During the last decade, possibilities to realize new phenomena and create new applications by varying system properties in time have gained increasing attention in many research fields.

Update: Tigramite now has a new CausalEffects class that allows to estimate (conditional) causal effects and mediation based on assuming a causal graph. Have a look at the tutorial. Further, Tigramite ...

Subscribe! Want more math video lessons? Visit my website to view all of my math videos organized by course, chapter and section. The purpose of posting my free video tutorials is to not only help ...

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

Captum is a model interpretability and understanding library for PyTorch. Captum means comprehension in Latin and contains general purpose implementations of integrated gradients, saliency maps, ...

When planning experimental research, determining an appropriate sample size and using suitable statistical models are crucial for robust and informative results. The recent replication crisis ...

Ground-based applications of robotics and autonomous systems (RASs) are fast advancing, and there is a growing appetite for developing cost-effective RAS solutions for in situ servicing, debris ...

Mixed-effects models are a powerful tool for modeling fixed and random effects simultaneously, but do not offer a feasible analytic solution for estimating the probability that a test correctly ...