InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand...
We did this by fitting several models, each with a different input tree (with the function brm_multiple()), and merging posterior samples. In all models, we also included a second random effect to account for multiple measures from each species. Continuous predictors were scaled (the mean ...
andcontemporarysciencestudiesthatviewscienceaslargelyamatterofpower.Drawingontheoriesofdistributedcomputingandartificialintelligence,PaulThagarddevelopsnewmodelsthatmakesenseofscientificchangeasacomplexsystemofcognitive,social,andphysicalinteractions.Thisisabookthatwillappealtoallreaderswithaninterestinthedevelopmentofscienceand...
and has the potential to generate simpler unifying models that can explain giving behavior under different contexts. Moreover, the fact that social norms are followed differently between contexts should influence the way norms are currently modelled in utility-maximizing frameworks. For experimentalists an...
In numerous physical models on networks, dynamics are based on interactions that exclusively involve properties of a node’s nearest neighbors. However, a node’s local view of its neighbors may systematically bias perceptions of network connectivity or the prevalence of certain traits. We investigate...
The relationship between plant productivity and species richness is one of the most debated and important issues in ecology. Ecologists have found numerous forms of this relationship and its underlying processes. However, theories and proposed drivers ha
WT5?! Training Text-to-Text Models to Explain their Predictions Sharan Narang∗ Colin Raffel∗ Adam Roberts Noah Fiedel Google Research Katherine Lee Karishma Malkan Abstract Neural networks have recently achieved human-level performance on various challenging natural language Neural network WT5 (...
Firstly, the latter is a full hazard calculation that blends full distributions of the inputs, in particular the alternative ground-motion and seismogenic source models. Secondly, the hazard calculation with Open- Quake uses extensive ruptures for large magnitudes, which when combined with permissible...
We counted numbers of unique pLoF, missense, and synonymous variants in UKB in each quintile of the coding sequence (CDS) of all protein-coding genes and clustered the variants using Gaussian mixture models. We limited the analyses to genes with ≥ 5 variants of each type (16,473 genes)....
visual inspection of the actual vs. fitted plot and goodness-of-fit tests indicate that the models are well specified. This is also supported when considering the differences between the AIC models for individual models estimated with/without sentiment variables. For each DV, the difference is grea...