Publication bias adjustment in network meta-analysis: an inverse probability weighting approach using clinical trial registries

Kavli Affiliate: Yi Zhou | First 5 Authors: Ao Huang, Yi Zhou, Satoshi Hattori, , | Summary: Network meta-analysis (NMA) is a useful tool to compare multiple interventions simultaneously in a single meta-analysis, it can be very helpful for medical decision making when the study aims to find the best therapy among several active candidates. […]


Continue.. Publication bias adjustment in network meta-analysis: an inverse probability weighting approach using clinical trial registries

Chirality-induced Phonon-Spin Conversion at an Interface

Kavli Affiliate: Mamoru Matsuo | First 5 Authors: Takumi Funato, Mamoru Matsuo, Takeo Kato, , | Summary: We consider spin injection driven by nonequilibrium chiral phonons from a chiral insulator into an adjacent metal. Phonon-spin conversion arises from the coupling of the electron spin with the microrotation associated with chiral phonons. We derive a microscopic […]


Continue.. Chirality-induced Phonon-Spin Conversion at an Interface

Chirality-induced Phonon-Spin Conversion at an Interface

Kavli Affiliate: Mamoru Matsuo | First 5 Authors: Takumi Funato, Mamoru Matsuo, Takeo Kato, , | Summary: We consider spin injection driven by nonequilibrium chiral phonons from a chiral insulator into an adjacent metal. Phonon-spin conversion arises from the coupling of the electron spin with the microrotation associated with chiral phonons. We derive a microscopic […]


Continue.. Chirality-induced Phonon-Spin Conversion at an Interface

Machine learning for industrial sensing and control: A survey and practical perspective

Kavli Affiliate: Biao Huang | First 5 Authors: Nathan P. Lawrence, Seshu Kumar Damarla, Jong Woo Kim, Aditya Tulsyan, Faraz Amjad | Summary: With the rise of deep learning, there has been renewed interest within the process industries to utilize data on large-scale nonlinear sensing and control problems. We identify key statistical and machine learning […]


Continue.. Machine learning for industrial sensing and control: A survey and practical perspective

The Emergence of Antiferromagnetic Correlations and Kondo-like Features in a Two-Band Model for Infinite-Layer Nickelates

Kavli Affiliate: Cheng Peng | First 5 Authors: Fangze Liu, Cheng Peng, Edwin W. Huang, Brian Moritz, Chunjing Jia | Summary: We report a determinant quantum Monte Carlo study of a two-band model, inspired by infinite-layer nickelates, focusing on the influence of interlayer hybridization between $3d_{x^2-y^2}$ orbitals derived from Ni (or Ni and O) in […]


Continue.. The Emergence of Antiferromagnetic Correlations and Kondo-like Features in a Two-Band Model for Infinite-Layer Nickelates

The emergence of antiferromagnetic correlations and Kondo-like features in a two-band model for infinite-layer nickelates

Kavli Affiliate: Cheng Peng | First 5 Authors: Fangze Liu, Cheng Peng, Edwin W. Huang, Brian Moritz, Chunjing Jia | Summary: We report a determinant quantum Monte Carlo study of a two-band model, inspired by infinite-layer nickelates, focusing on the influence of interlayer hybridization between $3d_{x^2-y^2}$ orbitals derived from Ni (or Ni and O) in […]


Continue.. The emergence of antiferromagnetic correlations and Kondo-like features in a two-band model for infinite-layer nickelates

Enhancing In-context Learning via Linear Probe Calibration

Kavli Affiliate: Yi Zhou | First 5 Authors: Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz | Summary: In-context learning (ICL) is a new paradigm for natural language processing that utilizes Generative Pre-trained Transformer (GPT)-like models. This approach uses prompts that include in-context demonstrations to generate the corresponding output for a new query […]


Continue.. Enhancing In-context Learning via Linear Probe Calibration