283 research outputs found
Influence of the borohydride concentration on the composition of the amorphous Fe-B alloy produced by chemical reduction of synthetic, nano-sized iron-oxide particles Part I: Hematite
A
Production of amorphous Fe-B alloy and alpha-Fe by chemical reduction of hematite using sodium borohydride
Influence of the borohydride concentration on the composition of the amorphous Fe-B alloy produced by chemical reduction of synthetic, nano-sized iron oxide particles Part II. Goethite
Bayesian Prompt Learning for Image-Language Model Generalization
Foundational image-language models have generated considerable interest due to their efficient adaptation to downstream tasks by prompt learning. Prompt learning treats part of the language model input as trainable while freezing the rest, and optimizes an Empirical Risk Minimization objective. However, Empirical Risk Minimization is known to suffer from distributional shifts which hurt generalizability to prompts unseen during training. By leveraging the regularization ability of Bayesian methods, we frame prompt learning from the Bayesian perspective and formulate it as a variational inference problem. Our approach regularizes the prompt space, reduces overfitting to the seen prompts and improves the prompt generalization on unseen prompts. Our framework is implemented by modeling the input prompt space in a probabilistic manner, as an a priori distribution which makes our proposal compatible with prompt learning approaches that are unconditional or conditional on the image. We demonstrate empirically on 15 benchmarks that Bayesian prompt learning provides an appropriate coverage of the prompt space, prevents learning spurious features, and exploits transferable invariant features. This results in better generalization of unseen prompts, even across different datasets and domains. Code available at: https://github.com/saic-fi/Bayesian-Prompt-Learnin
Perfil da assistência odontológica pública para a infância e adolescência em São LuÃs (MA)
Quark Number Susceptibility with Finite Chemical Potential in Holographic QCD
We study the quark number susceptibility in holographic QCD with a finite
chemical potential or under an external magnetic field at finite temperature.
We first consider the quark number susceptibility with the chemical potential.
We observe that approaching the critical temperature from high temperature
regime, the quark number susceptibility divided by temperature square develops
a peak as we increase the chemical potential, which confirms recent lattice QCD
results. We discuss this behavior in connection with the existence of the
critical end point in the QCD phase diagram. We also consider the quark number
susceptibility under the external magnetic field. We predict that the quark
number susceptibility exhibits a blow-up behavior at low temperature as we
raise the value of the magnetic field. We finally spell out some limitations of
our study.Comment: 25 pages, 3 figures, published versio
Evaluation of insulin-like growth factor-I in postmenopausal women with breast cancer treated with raloxifene
Scientific production on workplace bullying/harassment in dissertations and theses in the Brazilian scenario
Registro de ações para prevenção de morbidade infantil na caderneta de saúde da criança
- …