Gradium released two real-time speech translation models, stt-translate and s2s-translate, covering English, French, German, Spanish, and Portuguese across 20 language pairs. The models collapse the ...

WiFi CSI signals encode a rich manifold of environmental and human information: room geometry via multipath reflections, human body configuration via Fresnel zone perturbations, and temporal dynamics ...

The subtype composition of seasonal influenza waves varies in space and time. Influenza subtypes A/H1N1, A/H3N2 and B tend to have different impacts on population groups; therefore, understanding the ...

👉 Complete articles on Geometric Deep Learning, Graph Neural Networks, Topological Data Analysis with exercises are available on my Substack newsletter Hands-on Geometric Deep Learning The authors ...

GraphStorm is an enterprise-grade graph machine learning (GML) framework designed for scalability and ease of use. It simplifies the development and deployment of GML models on industry-scale graphs ...

Deep-learning throughput hinges on how effectively a compiler stack maps tensor programs to GPU execution: thread/block schedules, memory movement, and instruction selection (e.g., Tensor Core MMA ...

A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...

We show how random feature maps can be used to forecast dynamical systems with excellent forecasting skill. We consider the tanh activation function and judiciously choose the internal weights in a ...

Time series modelling involves processing data, analysing it, and applying various tests before developing the model. The ARIMA model consists of Auto-Regressive, Integrated, and Moving Averages ...

VAR models are different from univariate autoregressive models because they allow analysis and make predictions on multivariate time series data. Vector autoregression (VAR) is a statistical model for ...