Results 141 to 150 of about 4,379,261 (288)

Comparative evaluation of linear and nonlinear dimensionality reduction techniques for breast cancer diagnosis

Scientific Reports
Dimensionality reduction plays a crucial role in improving the interpretability and structural visualization of machine learning configurations applied to high-dimensional biomedical data. This study presents an exploratory comparative evaluation of four
Ahlam Labdaoui, Soundes Mekki
doaj   +1 more source

Ion‐Reconfigurable “N”‐Shaped Antiambipolar Behavior in Organic Electrochemical Transistors

Advanced Materials, EarlyView.
A unique N‐shaped negative differential transconductance (NDT) characteristics is demonstrated in single‐polymer organic electrochemical transistors through a sequential doping–redox–doping process driven by iodide ions. This redox‐driven mechanism enables low‐voltage, ion‐controlled reconfigurability and tunable current modulation, allowing seamless ...
Debdatta Panigrahi, Daniele Zucchelli, Zeinab Hamid, Christina Kousseff, Arup Sarkar, Aristea Pavlou, Zhitian Ling, Somayeh Kashani, Iain McCulloch, Paul W. M. Blom, Fabrizio Torricelli, Paschalis Gkoupidenis   +11 more
wiley   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Path‐Decoupled Cation‐Eutaxy III–V van der Waals Memristive Semiconductors for Mitigating the Neuromorphic Accuracy‐Energy Trade‐off

Advanced Materials, EarlyView.
Path‐decoupled III–V van der Waals memtransistors spatially separate ionic and electronic transport to overcome the conventional trade‐off between accuracy and energy in neuromorphic hardware. Mobile K+ ions in the vdW gaps set a wide conductance window, Gmax/Gmin, while gate‐tunable hole conduction lowers programming energy, enabling reliable ...
Jihong Bae, Ji Hoon Han, Taeyoung Kim, Jongbum Won, Seokmin Park, Gyu Won Kim, Sungsoon Kim, Hong Choi, Taehoon Kim, Hong‐Sub Lee, Jae‐Hyun Lee, Young Jin Choi, Jinwoo Cheon, Wooyoung Shim   +13 more
wiley   +1 more source

Pulsed Laser‐Assisted Phase Engineering of Multimetallic Colloidal Nanocrystals With Complex Compositions

Advanced Materials, EarlyView.
The engineering of colloidal nanocrystals with complex compositions has emerged as a highly active area of research within nanomaterials science. This review covers key aspects of colloidal solid‐solution nanocrystal formation using pulsed laser irradiation.
Marina T. Candela, Sergio Triviño‐Sánchez, Andrés Guerrero‐Martínez, Luis M. Liz‐Marzán, Guillermo González‐Rubio   +4 more
wiley   +1 more source

Descriptors to Dynamics: A Materials and Device Perspective on in‐Materio Physical Reservoir Computing for Neuromorphic Edge Intelligence

Advanced Materials, EarlyView.
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh, Alif Syafiq Kamarol Zaman, Muzhen Xu, Yuki Usami, Saptarshi Das, Hirofumi Tanaka   +5 more
wiley   +1 more source

Nonlinear dimensionality reduction methods for synthetic biology biobricks' visualization. [PDF]

BMC Bioinformatics, 2017
Yang J, Wang H, Ding H, An N, Alterovitz G.   +4 more
europepmc   +1 more source

Dimensionality reduction on vector spaces using complex random matrices

reservedIn this thesis we present part of a wider work regarding dimensionality reduction on the Euclidean space. Specifically we focus on finding concentration bounds for sums of Rademacher Chaoses.
MORETTI, SIMONE
core  

Nonlinear dimensionality reduction methods in climate data analysis

, 2008
Linear dimensionality reduction techniques, notably principal component analysis, are widely used in climate data analysis as a means to aid in the interpretation of datasets of high dimensionality.
Ross, Ian
core