Results 71 to 80 of about 3,282,089 (344)

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

De Novo Multi‐Mechanism Antimicrobial Peptide Design via Multimodal Deep Learning

Advanced Science, EarlyView.
Current AI‐driven peptide discovery often overlooks complex structural data. This study presents M3‐CAD, a generative pipeline that leverages 3D voxel coloring and a massive database of over 12 000 peptides to capture nuanced physicochemical contexts.
Xiaojuan Li, Haifan Gong, Yue Wang, Yinuo Zhao, Lixiang Li, Peijing Bao, Qingzhou Kong, Jialu Fu, Boyao Wan, Yumeng Zhang, Jinghui Zhang, Jiekun Ni, Zhongxue Han, Xueping Nan, Kunping Ju, Longfei Sun, Yuerui Ma, Huijun Chang, Mengqi Zheng, Yanbo Yu, Xiaoyun Yang, Xiuli Zuo, Haina Wang, Yanqing Li   +23 more
wiley   +1 more source

Using large language models to accelerate communication for eye gaze typing users with ALS

Nature Communications
Accelerating text input in augmentative and alternative communication (AAC) is a long-standing area of research with bearings on the quality of life in individuals with profound motor impairments.
Shanqing Cai, Subhashini Venugopalan, Katie Seaver, Xiang Xiao, Katrin Tomanek, Sri Jalasutram, Meredith Ringel Morris, Shaun Kane, Ajit Narayanan, Robert L. MacDonald, Emily Kornman, Daniel Vance, Blair Casey, Steve M. Gleason, Philip Q. Nelson, Michael P. Brenner   +15 more
doaj   +1 more source

Bridging the Privacy Accounting Gap in DP-SGD

The Journal of Privacy and Confidentiality
Differentially Private Stochastic Gradient Descent (DP-SGD) is one of the most widely used algorithms for private machine learning. Due to its efficiency, most practical implementations of DP-SGD shuffle the training examples and divide them into fixed ...
Lynn Chua, Badih Ghazi, Charlie Harrison, Ethan Leeman, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang   +8 more
doaj   +1 more source

Caravan - A global community dataset for large-sample hydrology

Scientific Data, 2023
High-quality datasets are essential to support hydrological science and modeling. Several CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets exist for specific countries or regions, however these datasets lack standardization,
Frederik Kratzert, Grey Nearing, Nans Addor, Tyler Erickson, Martin Gauch, Oren Gilon, Lukas Gudmundsson, Avinatan Hassidim, Daniel Klotz, Sella Nevo, Guy Shalev, Yossi Matias   +11 more
doaj   +1 more source

An Introduction to Google Scholar [PDF]

, 2019
This handout discusses the pros and cons of using Google Scholar to find books and journal articles. It tells how to connect Google Scholar to our Jerry Falwell Library subscription databases.
Miller, Randy L
core   +1 more source

An Open‐Source Pipeline for Calcium Imaging and All‐Optical Physiology in Human Stem Cell‐Derived Neurons

Advanced Science, EarlyView.
This work introduces an open‐source all‐optical platform for functional phenotyping of human stem cell‐derived neurons. The system integrates optogenetics, calcium imaging, automated acquisition, and analysis to resolve single‐cell and network activity, enabling longitudinal measurements, disease modeling, and pharmacological screening in preclinical ...
Wardiya Afshar‐Saber, Federico M. Gasparoli, Ziqin Yang, Nicole A. Teaney, Rachel Hobson, Lahin Lalani, Gayathri Srinivasan, Dosh Whye, Ranit Karmakar, Elizabeth D. Buttermore, Kellen D. Winden, Cidi Chen, Mustafa Sahin   +12 more
wiley   +1 more source

A mobile-optimized artificial intelligence system for gestational age and fetal malpresentation assessment

Communications Medicine, 2022
Gomes et al. develop machine learning models for gestational age and fetal malpresentation assessment on fetal ultrasound. The authors optimize their system for use in low-resource settings, using novice ultrasound operators, simplified imaging protocols,
Ryan G. Gomes, Bellington Vwalika, Chace Lee, Angelica Willis, Marcin Sieniek, Joan T. Price, Christina Chen, Margaret P. Kasaro, James A. Taylor, Elizabeth M. Stringer, Scott Mayer McKinney, Ntazana Sindano, George E. Dahl, William Goodnight, Justin Gilmer, Benjamin H. Chi, Charles Lau, Terry Spitz, T. Saensuksopa, Kris Liu, Tiya Tiyasirichokchai, Jonny Wong, Rory Pilgrim, Akib Uddin, Greg Corrado, Lily Peng, Katherine Chou, Daniel Tse, Jeffrey S. A. Stringer, Shravya Shetty   +29 more
doaj   +1 more source

Deep AutoRegressive Networks [PDF]

, 2014
We introduce a deep, generative autoencoder capable of learning hierarchies of distributed representations from data. Successive deep stochastic hidden layers are equipped with autoregressive connections, which enable the model to be sampled from quickly
Andriy Mnih, Charles Blundell, Daan Wierstra, Google Deepmind, Ivo Danihelka, Karol Gregor   +5 more
core   +2 more sources

A Perspective on Interactive Theorem Provers in Physics

Advanced Science, EarlyView.
Into an interactive theorem provers (ITPs), one can write mathematical definitions, theorems and proofs, and the correctness of those results is automatically checked. This perspective goes over the best usage of ITPs within physics and motivates the open‐source community run project PhysLean, the aim of which is to be a library for digitalized physics
Joseph Tooby‐Smith
wiley   +1 more source