Results 201 to 210 of about 2,848,958 (338)
Distinct Biotypes of Visual Perception in Major Depressive Disorder
In a discover dataset (272 acute MDD patients), this work identifies a novel depression biotype characterized by impaired visual motion perception, using machine learning clustering. An independent dataset confirms the robustness of this biotype through cross‐validation and demonstrates its generalizability.
Zhuoran Cai +13 more
wiley +1 more source
Interpretable Sensor Change Detection via Conditional Cauchy-Schwarz Divergence. [PDF]
Wang W, Shen Y, Ni Y, Wu W.
europepmc +1 more source
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang +6 more
wiley +1 more source
Kernel mean matching enhances risk estimation under spatial distribution shifts. [PDF]
Serov E, Koldasbayeva D, Zaytsev A.
europepmc +1 more source
Physical reservoir computing (PRC) based on spin wave interference has demonstrated high computational performance, yet room for improvement remains. In this study, we fabricated this concept PRC with eight detectors and evaluated the impact of the number of detectors using a chaotic time series prediction task.
Sota Hikasa +6 more
wiley +1 more source
Integrating Line Transect Distance Sampling and Spatial Analysis to Assess Local Density and Habitat Use of <i>Capra aegagrus</i> in Batman Province, Türkiye. [PDF]
Yıldırım E, Ulutürk S.
europepmc +1 more source
Blur kernel estimation using normalized color-line priors
Wei-Sheng Lai +3 more
semanticscholar +1 more source
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin +7 more
wiley +1 more source
Photovoltaic power interval prediction with conditional error dependency using Bayesian optimized deep learning. [PDF]
Chen Y, Wang X, Huang R, You G.
europepmc +1 more source
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu +6 more
wiley +1 more source

