There are also trade-offs in creativity. Because the energy critic favors low-energy (i.e., high-probability) text, the model ...

Autoregressive models are a statistical technique used to predict future values in a sequence based on its past values. It is essentially a fancy way of saying that it uses the past to predict the ...

Additive manufacturing of alloys has enabled the creation of machine parts that meet the complex requirements needed to ...

Spatial econometrics addresses the challenges posed by spatially correlated data, enabling researchers to understand and quantify how economic phenomena in one location can influence those in ...

Physical Autoregressive Model for Robotic Manipulation without Action Pretraining Recently, a new “Physical Autoregressive ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 28, No. 3 (Sep., 2000), pp. 605-613 (9 pages) The authors give easy-to-check sufficient conditions for the geometric ...

This article introduces a new model called the buffered autoregressive model with generalized autoregressive conditional heteroscedasticity (BAR-GARCH). The proposed model, as an extension of the BAR ...

During the 2025 Inclusion Bund Conference, Ant Group and Renmin University of China jointly released the industry's first native MoE architecture diffusion language model (dLLM) 'LLaDA-MoE' in ...

Given the importance and the ubiquity of indoor spaces in our everyday lives, the ability to have computer models which can understand, model, and synthesize indoor scenes is of vital importance for ...