Institution profile

Norwegian University of Life Sciences

Academic institutioneurope · no
Official website
Research library14linked papers
Opportunities0open roles
Selected work

Representative Papers

CAST: Closed-form Analytic Semantic Transfer for Zero-Shot Classifier Extension

Aug 13, 2026

This study addresses the absence of target samples in zero-shot learning by proposing a training-free, image-free analytical semantic transfer framework. Through a closed-form weight injection mechanism, pretrained classifiers are extended to unseen categories without iterative optimization. Furthermore, this work establishes a finite-sample error decomposition theory and introduces a computable semantic extrapolation residual metric to guide data construction. Empirical evaluations on standard benchmarks demonstrate that the proposed method matches or surpasses existing image-free approaches while approaching few-shot performance levels. Collectively, this framework provides an efficient analytical solution with rigorous theoretical support for zero-shot learning, effectively bridging the gap between training-free efficiency and high-accuracy generalization in the absence of visual data.

0 citationsRead paper

Bayesian Fractional Polynomials for Optimal Dosage Estimation with Fish Nutrition Applications

May 07, 2026

This study addresses the challenge of estimating optimal doses in nonlinear dose–response relationships, particularly in contexts such as aquaculture, by introducing a Bayesian fractional polynomial framework for the first time. The proposed approach explicitly quantifies and integrates model uncertainty through Bayesian model averaging, thereby enhancing the robustness and accuracy of optimal dose estimation. In simulation studies, the method significantly outperforms existing benchmark approaches. Furthermore, when applied to real-world data on fish nutritional requirements, it successfully identifies the optimal nutrient dose level, demonstrating both practical applicability and statistical reliability.

0 citationsRead paper
Recent publications

Latest Papers

CAST: Closed-form Analytic Semantic Transfer for Zero-Shot Classifier Extension

Aug 13, 2026

This study addresses the absence of target samples in zero-shot learning by proposing a training-free, image-free analytical semantic transfer framework. Through a closed-form weight injection mechanism, pretrained classifiers are extended to unseen categories without iterative optimization. Furthermore, this work establishes a finite-sample error decomposition theory and introduces a computable semantic extrapolation residual metric to guide data construction. Empirical evaluations on standard benchmarks demonstrate that the proposed method matches or surpasses existing image-free approaches while approaching few-shot performance levels. Collectively, this framework provides an efficient analytical solution with rigorous theoretical support for zero-shot learning, effectively bridging the gap between training-free efficiency and high-accuracy generalization in the absence of visual data.

0 citationsRead paper

Bayesian Fractional Polynomials for Optimal Dosage Estimation with Fish Nutrition Applications

May 07, 2026

This study addresses the challenge of estimating optimal doses in nonlinear dose–response relationships, particularly in contexts such as aquaculture, by introducing a Bayesian fractional polynomial framework for the first time. The proposed approach explicitly quantifies and integrates model uncertainty through Bayesian model averaging, thereby enhancing the robustness and accuracy of optimal dose estimation. In simulation studies, the method significantly outperforms existing benchmark approaches. Furthermore, when applied to real-world data on fish nutritional requirements, it successfully identifies the optimal nutrient dose level, demonstrating both practical applicability and statistical reliability.

0 citationsRead paper