Results 121 to 130 of about 6,336,923 (296)
Opportunistic Dynamic Architecture for Class-Incremental Learning
IEEE AccessContinual learning has attracted increasing attention over the last few years, as it enables to continually learn new tasks over time, which has significant implication to many real-world applications.
Fahrurrozi Rahman +2 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.The hydration behavior of C3S in seawater‐relevant solutions is studied based on experiments, boundary nucleation and growth (BNG) modeling, and machine learning. The main ions included in seawater modify hydration mechanisms, with MgCl2 showing the strongest acceleration effect at the same concentration.
Yanjie Sun +6 more
wiley +1 more source
Eigenvector Continuation with Subspace Learning
Physical Review Letters, 2018 Version to appear in Physical Review Letters, 4 + 6 pages (main + supplemental materials), 1 + 6 figures (main + supplemental materials)
Frame, Dillon +5 more
openaire +4 more sources
Probing Machine Learning Interatomic Potentials on Ion Transport Properties
Advanced Intelligent Discovery, EarlyView.We perform a systematic benchmark of six state‐of‐the‐art universal machine learning interatomic potentials on their ability to predict ion transport properties in lithium‐ and sodium‐based superionic conductors relevant to all‐solid‐state batteries.
Ogheneyoma Aghoghovbia +2 more
wiley +1 more source
Continual Learning for User Identification and Game Classification Based on Virtual Reality Headset Data: Applications on the Questset Dataset [PDF]
openUser identification is a fundamental component for enabling personalization and adaptive interactions in Virtual Reality (VR) systems. This thesis investigates the applicability of Continual Learning (CL) methods to user identification.
PIZZOLOTTO, ANDREA
core
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo +3 more
wiley +1 more source
Open-world continual learning: Unifying novelty detection and continual learning
Artificial IntelligenceAs AI agents are increasingly used in the real open world with unknowns or novelties, they need the ability to (1) recognize objects that (a) they have learned before and (b) detect items that they have never seen or learned, and (2) learn the new items incrementally to become more and more knowledgeable and powerful. (1) is called novelty detection or
Gyuhak Kim +4 more
openaire +5 more sources
Advanced Intelligent Systems, EarlyView.A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha +2 more
wiley +1 more source
Continual Unsupervised Representation Learning
CoRR, 2019 NeurIPS ...
Rao, D +5 more
openaire +5 more sources
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
Advanced Intelligent Systems, EarlyView.Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica +38 more
wiley +1 more source