Results 141 to 150 of about 21,351 (259)

Exploiting explanations for model extraction via knowledge distillation and mitigation with private counterfactuals. [PDF]

Front Artif Intell
Ezzeddine F, Giordano S, Ayoub O.
europepmc   +1 more source

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source

Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation. [PDF]

Measurement (Lond)
Jeon ES, Lee J, Lim H, Save OM, Lee H, Turaga P.   +5 more
europepmc   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Deep Guided Exposure Correction with Knowledge Distillation. [PDF]

Sensors (Basel)
Liu S, Zhang T.
europepmc   +1 more source

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

Advanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang, Abudukadi Tudi, Ran An, Zhihua Yang   +3 more
wiley   +1 more source

IMFLKD: an incentive mechanism for decentralized federated learning based on knowledge distillation. [PDF]

Sci Rep
Ying X, Yan K, Gao X, Huang J.
europepmc   +1 more source

Haptic In‐Sensor Computing Device Based on CNT/PDMS Nanocomposite Physical Reservoir

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Using a porous carbon nanotube‐polydimethylsiloxane nanocomposite, a sensor array integrated with a physical reservoir computing paradigm capable of in‐sensor computing is demonstrated. The device is able to classify between nine objects with an accuracy above 80%, opening the possibility for low‐power sensing/computing for future robotics.
Kouki Kimizuka, Saman Azhari, Shoshi Tokuno, Ahmet Karacali, Yuki Usami, Shuhei Ikemoto, Hakaru Tamukoh, Hirofumi Tanaka   +7 more
wiley   +1 more source

HKD-CPI: high-order knowledge distillation enhanced inductive compound-protein interaction prediction. [PDF]

Bioinformatics
He Z, Liu X, Jiang Y, Xu J, Lin Y, Jin S, Wei L, Wang Y.   +7 more
europepmc   +1 more source

Implantation‐On‐Chip: An AI‐Based Platform for Monitoring the Embryo Trophoblast–Endometrial Stroma Cross Talk With Xenobiotics Interference

Advanced Intelligent Systems, EarlyView.
We present a novel AI‐integrated implantation‐on‐chip platform that enables mimicking and monitoring the maternal–fetal interactions at the early phases of human embryo implantation with high spatiotemporal resolution. The complexity of the trophoblast invasion process was addressed by conducting the analysis at global (rate of invasion) and local ...
Joanna Filippi, Valentina Lacconi, Arianna Mencattini, Micol Massimiani, Dolores Lobresca, Gaia Posanzini, Alessia Riccardi, Paola Casti, Michele D’Orazio, Gianni Antonelli, Giorgia Curci, Luisa Campagnolo, Eugenio Martinelli   +12 more
wiley   +1 more source