Abstract: In the classic machine learning framework, models are trained on historical data and used to predict future values. It is assumed that the data distribution does not change over time ...

So far, running LLMs has required a large amount of computing resources, mainly GPUs. Running locally, a simple prompt with a typical LLM takes on an average Mac ...

Abstract: State estimation for nonlinear models has been a longstanding challenge in the field of signal processing. Classical nonlinear filters, such as the extended Kalman filter (EKF), unscented ...

An exercise-driven course on Advanced Python Programming that was battle-tested several hundred times on the corporate-training circuit for more than a decade. Written by David Beazley, author of the ...

We present MELLE, a novel continuous-valued tokens based language modeling approach for text to speech synthesis (TTS). MELLE autoregressively generates continuous mel-spectrogram frames directly from ...