Results 201 to 210 of about 55,131 (288)

GPU-Accelerated Implementation of Constant-pH Molecular Dynamics in NAMD. [PDF]

J Chem Inf Model
Moe S, Chipot C, Roux B.
europepmc   +1 more source

KDLM: Lightweight Brain Tumor Segmentation via Knowledge Distillation

Advanced Intelligent Systems, EarlyView.
A lightweight student network is designed, which is based on multiscale and multilevel feature fusion and combined with the residual channel attention mechanism to achieve efficient feature extraction and fusion with very few parameters. A dual‐teacher collaborative knowledge distillation framework is proposed.
Baotian Li, Haoyu Tang, Jun Zhu, Fang Fang Gou, Jia Wu   +4 more
wiley   +1 more source

Accelerated susceptibility-driven positive contrast MRI reconstruction based on primal-dual optimization with minimal parameter tuning. [PDF]

Quant Imaging Med Surg
Shi C, Cheng J, Lu N, Deng X, Wang Q.
europepmc   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

CCC-GPU: a graphics processing unit (GPU)-accelerated nonlinear correlation coefficient for large-scale transcriptomic analyses. [PDF]

Bioinformatics
Zhang H, Fotso KT, Subirana-Granés M, Pividori M.   +3 more
europepmc   +1 more source

A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks

Advanced Intelligent Systems, EarlyView.
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan, Oliver Artner, Paul‐Philipp Manea, Sebastian Siegel, Susanne Hoffmann‐Eifert, Regina Dittmann, John Paul Strachan   +6 more
wiley   +1 more source

SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs. [PDF]

Bioinformatics
Rodriguez A, Kim Y, Nandi TN, Keat K, Kumar R, Conery M, Bhukar R, Liu M, Hessington J, Maheshwari K, VA Million Veteran Program , Begoli E, Tourassi G, Muralidhar S, Natarajan P, Voight BF, Cho K, Gaziano JM, Damrauer SM, Liao KP, Zhou W, Huffman JE, Verma A, Madduri RK.   +23 more
europepmc   +1 more source

Artificial Intelligence in Autonomous Mobile Robot Navigation: From Classical Approaches to Intelligent Adaptation

Advanced Intelligent Systems, EarlyView.
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella, Angelo Cardellicchio, Cosimo Patruno, Massimiliano Nitti, Nicola Pedrocchi, Vito Renò   +5 more
wiley   +1 more source

Accelerating Catalyst Materials Discovery With Large Artificial Intelligence Models

Angewandte Chemie, EarlyView.
AI‐empowered catalysis research via integrated database platform, universal machine learning interatomic potentials (MLIPs), and large language models (LLMs). ABSTRACT The integration of artificial intelligence (AI) into catalysis is fundamentally reshaping the research paradigm of catalyst discovery.
Di Zhang, Yuanzheng Chen, Chuanyu Liu, Yan Liu, Hongliang Xin, Jiayu Peng, Pengfei Ou, Hao Li   +7 more
wiley   +2 more sources

Efficient calculation and analysis of dynamic RCS characteristics for moving target using the shooting and bouncing rays method. [PDF]

Sci Rep
Wu W, Ji J, Chen K, Chen G, Sun S, Guo Z, Ma Y.   +6 more
europepmc   +1 more source