Microorganisms including bacteria, fungi, viruses, protists and archaea live as communities
in complex and contiguous environments. They engage in numerous inter-and intra …

The recent explosion of interest in multimodal applications has resulted in a wide selection
of datasets and methods for representing and integrating information from different …

Voxel-based physiological (VBP) variables derived from blood oxygen level dependent
(BOLD) fMRI time-course variations include: amplitude of low frequency fluctuations (ALFF) …

Entropic causal inference is a recent framework for learning the causal graph between two
variables from observational data by finding the information-theoretically simplest structural …

In many machine learning systems that jointly learn from multiple modalities, a core research
question is to understand the nature of multimodal interactions: the emergence of new task …

Reliability-based design optimization (RBDO) is one of the most well-known methods to deal
with uncertainties in the design methods. There are still challenges with the application of …

We study causal discovery in a multi-environment setting, in which the functional relations
for producing the variables from their direct causes remain the same across environments …

Background Ecological interactions among microorganisms are fundamental for ecosystem
function, yet they are mostly unknown or poorly understood. High-throughput-omics can …

Existing reference-free turn-level evaluation metrics for chatbots inadequately capture the
interaction between the user and the system. Consequently, they often correlate poorly with …

The temporal evolution of microstructural features in metals and ceramics has been the
subject of intense investigation over many years because deviations from normal grain …