Search Results - Active learning Large Deviations Perception Model Message-passing algorithms

From pixels to planning: scale-free active inference.

Authors: Friston, Karl Heins, Conor Verbelen, Tim et al.

Source: Frontiers in Network Physiology; 2025, p1-37, 37p

Insilico discovery of tyrosinase-inhibiting natural products.

Authors: Wu, Xue Xu, Yuzhi Zhao, Ziqing et al.

Source: AIP Advances; Jul2025, Vol. 15 Issue 7, p1-12, 12p

Subject Terms: NATURAL products, HYPERPIGMENTATION, BIOACTIVE compounds, VIRTUAL high-throughput screening (Drug development), COMPUTATIONAL chemistry, SKIN diseases, PHENOL oxidase, DEEP learning

In Silico ADME Methods Used in the Evaluation of Natural Products.

Authors: Ancuceanu, Robert Lascu, Beatrice Elena Drăgănescu, Doina et al.

Source: Pharmaceutics; Aug2025, Vol. 17 Issue 8, p1002, 58p

Subject Terms: NATURAL products, PHARMACOKINETICS, COMPUTER simulation, MOLECULAR models, PHARMACEUTICAL industry, ALGORITHMS, DRUG discovery

Socializing AI: Integrating Social Network Analysis and Deep Learning for Precision Dairy Cow Monitoring—A Critical Review.

Authors: Parivendan, Sibi Chakravathy Sailunaz, Kashfia Neethirajan, Suresh

Source: Animals (2076-2615); Jul2025, Vol. 15 Issue 13, p1835, 48p

Subject Terms: ARTIFICIAL intelligence, DEEP learning, ETHICAL problems, PRECISION farming, DAIRY cattle, SOCIAL network analysis, ANIMAL welfare, SCIENTIFIC observation

Graph Neural Networks in Brain Connectivity Studies: Methods, Challenges, and Future Directions.

Authors: Mohammadi, Hamed Karwowski, Waldemar

Source: Brain Sciences (2076-3425); Jan2025, Vol. 15 Issue 1, p17, 24p

Subject Terms: GRAPH neural networks, LARGE-scale brain networks, DATA integration, GRAPH connectivity, CLINICAL neurosciences

An Active Inference Approach to Modeling Structure Learning: Concept Learning as an Example Case.

Authors: Smith, Ryan Schwartenbeck, Philipp Parr, Thomas et al.

Source: Frontiers in Computational Neuroscience; 5/19/2020, Vol. 14, p1-24, 24p

Subject Terms: CONCEPT learning, COMPUTATIONAL neuroscience, COGNITIVE learning, COGNITIVE science, STIMULUS generalization

Strong and weak head-related transfer functions: The eHRTF analytical framework.

Authors: Geronazzo, Michele

Source: JASA Express Letters; Aug2025, Vol. 5 Issue 8, p1-8, 8p

Edge-Driven Multi-Agent Reinforcement Learning: A Novel Approach to Ultrasound Breast Tumor Segmentation.

Authors: Karunanayake, Nalan Moodleah, Samart Makhanov, Stanislav S.

Source: Diagnostics (2075-4418); Dec2023, Vol. 13 Issue 24, p3611, 23p

Subject Terms: REINFORCEMENT learning, BREAST ultrasound, BREAST tumors, ARTIFICIAL neural networks, DEEP reinforcement learning

Learning Generative State Space Models for Active Inference.

Authors: Çatal, Ozan Wauthier, Samuel De Boom, Cedric et al.

Source: Frontiers in Computational Neuroscience; 11/16/2020, Vol. 14, pN.PAG-N.PAG, 17p

Subject Terms: ROBOTICS, ARTIFICIAL neural networks

Improving COVID‐19 Detection Through Cooperative Deep‐Learning Pipeline for Lung Semantic Segmentation in Medical Imaging.

Authors: Mourdi, Youssef Allioui, Hanane Sadgal, Mohamed

Source: International Journal of Imaging Systems & Technology; Sep2024, Vol. 34 Issue 5, p1-18, 18p

Dynamic Neighborhood Selection for Context Aware Temporal Evolution Using Graph Neural Networks.

Authors: Zeb, Muhammad Ali Uddin, M. Irfan Alarood, Ala Abdulsalam et al.

Source: Cognitive Computation; Feb2025, Vol. 17 Issue 1, p1-19, 19p

Coordination and control – limits in standard representations of multi-reservoir operations in hydrological modeling.

Authors: Rougé, Charles Reed, Patrick M. Grogan, Danielle S. et al.

Source: Hydrology & Earth System Sciences; 2021, Vol. 25 Issue 3, p1365-1388, 24p

Subject Terms: FLOOD warning systems, WATER shortages, LARGE deviations (Mathematics), SENSITIVITY analysis, WATER use

Machine learning and deep learning in data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry.

Authors: Kumar, Sethu Arun Ananda Kumar, Thirumoorthy Durai Beeraka, Narasimha M et al.

Source: Future Medicinal Chemistry; Feb2022, Vol. 14 Issue 4, p245-270, 26p

Diagnose Like a Radiologist: Hybrid Neuro-Probabilistic Reasoning for Attribute-Based Medical Image Diagnosis.

Authors: Zhao, Gangming Feng, Quanlong Chen, Chaoqi et al.

Source: IEEE Transactions on Pattern Analysis & Machine Intelligence; Nov2022, Vol. 44 Issue 11, p7400-7416, 17p

Subject Terms: DIAGNOSTIC imaging, DIAGNOSIS, X-ray imaging, MEDICAL logic, ARTIFICIAL neural networks, NEUROENDOCRINE cells, GRAPH algorithms, CHEST X rays

Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure.

Authors: Feldotto, Benedikt Eppler, Jochen Martin Jimenez-Romero, Cristian et al.

Source: Frontiers in Neuroinformatics; 5/19/2022, Vol. 16, p1-23, 23p

Subject Terms: WEB-based user interfaces, INFRASTRUCTURE (Economics), COMMUNICATION infrastructure, GRAPHICAL user interfaces, VIRTUAL machine systems, HIGH performance computing

Scientific discovery in the age of artificial intelligence.

Authors: Wang H Fu T Du Y et al.

Source: Nature [Nature] 2023 Aug; Vol. 620 (7972), pp. 47-60. Date of Electronic Publication: 2023 Aug 02.

Publication Type: Journal Article; Review; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, Non-U.S. Gov't

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 0410462 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1476-4687 (Electronic) Linking ISSN: 00280836 NLM ISO Abbreviation: Nature Subsets: MEDLINE

MeSH Terms: Artificial Intelligence*/standards , Artificial Intelligence*/trends , Research Design*/standards , Research Design*/trends, Datasets as Topic ; Deep Learning ; Unsupervised Machine Learning

Advances in Computational Approaches for Estimating Passive Permeability in Drug Discovery.

Authors: Bernardi, Austen Bennett, W. F. Drew He, Stewart et al.

Source: Membranes; Nov2023, Vol. 13 Issue 11, p851, 15p

Generative Models for Active Vision.

Authors: Parr, Thomas Sajid, Noor Da Costa, Lancelot et al.

Source: Frontiers in Neurorobotics; 4/13/2021, Vol. 15, pN.PAG-N.PAG, 20p

Subject Terms: EYE movements, VISION, PROPRIOCEPTION, SENSES

Inductive Multi-View Semi-supervised Learning with a Consensus Graph.

Authors: Ziraki, N. Bosaghzadeh, A. Dornaika, F. et al.

Source: Cognitive Computation; May2023, Vol. 15 Issue 3, p904-913, 10p

Diabetic Retinopathy Detection via Machine Learning and Deep Learning for Detected of Injury Dependence on CT Scan.

Authors: SULTAN, LAMAN R.

Source: International Journal of Pharmaceutical Research (09752366); Jan-Mar2021, Vol. 13 Issue 1, p5310-5321, 12p

Subject Terms: COMPUTED tomography, DIABETIC retinopathy, MACHINE learning, DEEP learning, WOUNDS & injuries