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 ...

Julia implementation for a family of 'classical' estimation approach of multi-variate time series model. Current applications includes vector autoregressive (VAR(p)) model and its relative estimation ...

ABSTRACT: We develop a model of sovereign default where borrowers’ physical capital is not observable by the lenders and therefore the bond price schedule does not depend on capital accumulation.

Every time a language model like GPT-4, Claude or Mistral generates a sentence, it does something deceptively simple: It picks one word at a time. This word-by-word approach is what gives ...

Vector Autoregression (VAR) is a statistical model used to capture the linear interdependencies among multiple time series data. It generalizes the univariate autoregressive model to multiple time ...

Autoregressive LLMs are complex neural networks that generate coherent and contextually relevant text through sequential prediction. These LLms excel at handling large datasets and are very strong at ...

Converting images into vector graphics or creating vector graphics is particularly useful if you need graphics for logos, illustrations, or print templates. While conventional image formats such as ...

Vector-borne diseases cause roughly 700,000 deaths worldwide every year. Vectors can carry different types of pathogens, including viruses and bacteria. Tropical and subtropical regions report large ...

The world of generative models has been revolutionized by the rise of diffusion models, capable of creating stunningly realistic images, videos, and even audio. While these models have achieved ...