Estimation techniques in computer vision applications must estimate accurate model parameters despite small-scale noise in the data, occasional large-scale measurement errors (outliers), and ...

Cacoullos and Papageorgiou (1982, in Statistics and Probability: Essays in Honor of C. R. Rao, G. Kallianpur et al. (eds), 155-168; Amsterdam: North-Holland) introduced and studied a three-parameter ...

Researchers at Freie Universität Berlin, University of Maryland and NIST, Google AI, and Abu Dhabi set out to robustly estimate the free Hamiltonian parameters of bosonic excitations in a ...

Introduction / William L Thompson -- PART ONE: OVERVIEW AND BASIC CONCEPTS -- Sampling rare populations / Lyman L. McDonald -- Separating components of detection probability in abundance estimation: ...

Google released its first Gemma 3 open models earlier this year, featuring between 1 billion and 27 billion parameters. In generative AI, the parameters are the learned variables that control how the ...

Researchers from Hebei University of Technology have developed an innovative approach to lithium-ion battery management that ...

Over the past two decades, the adoption of building information modeling (BIM) has steadily grown and become a more common industry practice. Traditionally utilized in the design and modeling phases ...

The BaGuaLu AI system used the Chinese Sunway exaflop supercomputer to train the largest AI model with over 174 trillion parameters. The miraculous capabilities of neural net AI systems like ChatGPT ...