Results 81 to 90 of about 76,158 (290)

Task‐Oriented Path Planning Towards Autonomous Sensor Network Deployment in Rainforest Canopies

Advanced Robotics Research, EarlyView.
An informative path planner for drone‐based deployment of wireless sensor networks in rainforest canopies is presented, addressing key challenges in large‐scale biodiversity monitoring. By integrating canopy surface detection with connectivity‐aware sampling under strict flight constraints, the approach enables efficient and reliable aerial sensor ...
Rita Santos Raminhos, Salua Hamaza
wiley   +1 more source

Fault-tolerant operation and materials science with neutral atom logical qubits

npj Quantum Information
We report on the fault-tolerant operation of logical qubits on a neutral atom quantum computer, with logical performance surpassing physical performance for multiple circuits including Bell state preparation (12x error reduction), random circuits (15x ...
Woo Chang Chung, Daniel C. Cole, Pranav Gokhale, Eric B. Jones, Kevin W. Kuper, David Mason, Victory Omole, Alexander G. Radnaev, Rich Rines, Mariesa H. Teo, Matt J. Bedalov, Matt Blakely, Peter D. Buttler, Caitlin Carnahan, Frederic T. Chong, Palash Goiporia, Bettina Heim, Garrett T. Hickman, Ryan A. Jones, Pradnya Khalate, Jin-Sung Kim, Martin T. Lichtman, Stephanie Lee, Nathan A. Neff-Mallon, Thomas W. Noel, Mark Saffman, Efrat Shabtai, Bharath Thotakura, Teague Tomesh, Angela K. Tucker   +29 more
doaj   +1 more source

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source

Stable Machine‐Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection‐Permitting Simulations

Journal of Advances in Modeling Earth Systems
Modern climate projections often suffer from inadequate spatial and temporal resolution due to computational limitations, resulting in inaccurate representations of sub‐grid processes.
Zeyuan Hu, Akshay Subramaniam, Zhiming Kuang, Jerry Lin, Sungduk Yu, Walter M. Hannah, Noah D. Brenowitz, Josh Romero, Michael S. Pritchard   +8 more
doaj   +1 more source

NVIDIA/cuQuantum: cuQuantum v22.05.0

, 2022
Documentation and full release notes for all versions are located here: https://docs.nvidia.com/cuda/cuquantum/index ...
sam-stanwyck, Leo Fang, hhbayraktar, ahehn-nv   +3 more
core   +1 more source

Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences

Advanced Science, EarlyView.
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu, Pan Zhang, Shangqian Wu, Hao Sun, Minwei Li, Sophia Tsoka, Zizhang Sheng, Lei Deng   +7 more
wiley   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers

Advanced Science, EarlyView.
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao, Misheng Cai, Zhenghong Wang, Yan Wang, Yuqi Li, Bo Dong, Hewu Wang, Andrew F. Burke, Simona Onori, Stephen J. Harris   +9 more
wiley   +1 more source

NVIDIA NVIDIA NCP-AAI PDF

The document titled "NVIDIA NCP-AAI PDF" serves as a comprehensive resource on NVIDIA's Advanced AI technologies and solutions. It encapsulates in-depth insights into various applications of AI within NVIDIA's frameworks, highlighting innovative features, technical specifications, and potential use cases in industries ranging from gaming to data ...
openaire   +1 more source

The 2018 NVIDIA AI City Challenge

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018
The NVIDIA AI City Challenge has been created to accelerate intelligent video analysis that helps make cities smarter and safer. With millions of traffic video cameras acting as sensors around the world, there is a significant opportunity for real-time and batch analysis of these videos to provide actionable insights. These insights will benefit a wide
Milind Naphade, Ming-Ching Chang, Anuj Sharma 0001, David C. Anastasiu, Vamsi Jagarlamudi, Pranamesh Chakraborty, Tingting Huang, Shuo Wang, Ming-Yu Liu 0001, Rama Chellappa, Jenq-Neng Hwang, Siwei Lyu   +11 more
openaire   +4 more sources