In many public healthcare systems, particularly in resource-constrained environments, time-series forecasting models offer a practical, interpretable, and evidence-based alternative (Stacey et al., ...

Meta Platforms Inc. today debuted an image generation model that can write code and search the web. Muse Image is the second ...

These are my go-to libraries for Python data crunching.

Tracing product flow Analyzing supplier dependencies Tracking supplier risks and dependency chains Understanding APIs (Active Pharmaceutical Ingredient) dependencies and connections Identifying risks ...

Every Python developer knows some or all of these libraries, because they’re stable, reliable, and excellent at what they do.

Abstract: Deep learning compilers optimize DNN program execution by capturing them as operator-based computation graphs. However, developers’ deep learning programs often contain complex Python ...

Abstract: Benefiting from the high-temporal resolution of electroencephalogram (EEG), EEG-based emotion recognition has become one of the hotspots of affective computing. For EEG-based emotion ...

StaR (Stateful Root Cause Analysis) is a deep learning framework for root cause analysis and causal discovery in dynamic multivariate time-series systems. This repository provides the official ...