Optimiz-rs provides blazingly fast, production-ready implementations of advanced optimization and statistical inference algorithms. Built with Rust for maximum performance and exposed to Python ...

There are many implemented methods to perform causal inference when your intervention of interest is binary, but few methods exist to handle continuous treatments. This is unfortunate because there ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Markov state models (MSM) are a popular statistical method for analyzing the ...

Inferring parameters of computational models that capture experimental data is a central task in cognitive neuroscience. Bayesian statistical inference methods usually require the ability to evaluate ...

The analysis of complex systems with many degrees of freedom generally involves the definition of low-dimensional collective variables more amenable to physical understanding. Their dynamics can be ...

The drift-diffusion model (DDM) is an important decision-making model in cognitive neuroscience. However, innovations in model form have been limited by methodological challenges. Here, we introduce ...

With the growing importance of microbiome research, there is increasing evidence that host variation in microbial communities is associated with overall host health. Advancement in genetic sequencing ...

The diffusion model is a commonly used tool to infer latent psychological processes underlying decision-making, and to link them to neural mechanisms based on response times. Although efficient open ...