Výsledky vyhľadávania - Theory of computation → Dynamic graph algorithms phrases Temporal constraint networks*

Agile Controllability of Simple Temporal Networks with Uncertainty and Oracles

Autori: Eder, Johann Posenato, Roberto Combi, Carlo a ďalší

Predmety: 2012 ACM Subject Classification Computing methodologies → Temporal reasoning, Theory of computation → Dynamic graph algorithms phrases Temporal constraint networks, contingent durations, agile controllability

Popis súboru: application/pdf

Relation: https://www.alexandria.unisg.ch/handle/20.500.14171/121953

Dostupnosť: https://doi.org/10.4230/LIPIcs.TIME.2024.1
https://www.alexandria.unisg.ch/handle/20.500.14171/121953
https://hdl.handle.net/20.500.14171/121953
https://doi.org/10.4230/LIPIcs.TIME.2024.4

A Primer on Deep Learning for Causal Inference.

Autori: Koch, Bernard J. Sainburg, Tim Geraldo Bastías, Pablo a ďalší

Zdroj: Sociological Methods & Research; May2025, Vol. 54 Issue 2, p397-447, 51p

Predmety: ARTIFICIAL neural networks, TREATMENT effect heterogeneity, CAUSAL inference, DEEP learning, ALGORITHMS

Further N -Frame networking dynamics of conscious observer-self agents via a functional contextual interface: predictive coding, double-slit quantum mechanical experiment, and decision-making fallacy modeling as applied to the measurement problem in humans and AI

Autori: Edwards, Darren J.

Zdroj: Frontiers in Computational Neuroscience; 2025, p1-53, 53p

Predmety: LANGUAGE models, ARTIFICIAL intelligence, COGNITIVE bias, QUANTUM operators, COGNITIVE maps (Psychology)

Idea Density and Grammatical Complexity as Neurocognitive Markers.

Autori: Iacono, Diego Feltis, Gloria C.

Zdroj: Brain Sciences (2076-3425); Sep2025, Vol. 15 Issue 9, p1022, 33p

Predmety: LINGUISTIC complexity, NEUROBIOLOGY, LINGUISTICS, COGNITIVE load, LANGUAGE & languages, DIAGNOSIS, COMPUTATIONAL linguistics

Osoby: CHOMSKY, Noam, 1928-

A Convergence of Theories of Mind and Brain.

Autori: Dubé, Chad Malmberg, Kenneth J.

Zdroj: Computational Brain & Behavior; Dec2025, Vol. 8 Issue 4, p649-670, 22p

A Data-Driven Framework for Flood Mitigation: Transformer-Based Damage Prediction and Reinforcement Learning for Reservoir Operations.

Autori: Tofighi, Soheyla Gurbuz, Faruk Mantilla, Ricardo a ďalší

Zdroj: Water (20734441); Oct2025, Vol. 17 Issue 20, p3024, 37p

Predmety: TRANSFORMER models, REINFORCEMENT learning, WATER storage, RISK assessment, HYDRAULIC models, EMPIRICAL research, FLOOD damage prevention

Geografický termín: UNITED States

Digital Twin Applications in the Water Sector: A Review.

Autori: Ghorbani Bam, Pooria Rezaei, Nader Roubanis, Alexander a ďalší

Zdroj: Water (20734441); Oct2025, Vol. 17 Issue 20, p2957, 49p

Predmety: DIGITAL twin, WATER management, REAL-time computing, PREDICTIVE control systems, RESOURCE allocation, RESOURCE management, ENVIRONMENTAL infrastructure

Machine Learning in Stream/River Water Temperature Modelling: a review and metrics for evaluation.

Autori: Corona, Claudia Rebecca Hogue, Terri Sue

Zdroj: Hydrology & Earth System Sciences Discussions; 8/26/2024, p1-38, 38p

Predmety: MACHINE learning, ARTIFICIAL intelligence, WATER temperature, STREAM function, COMPUTER simulation

Unravelling emotions: exploring deep learning approaches for EEG-based emotion recognition with current challenges and future recommendations.

Autori: Abgeena, Abgeena Garg, Shruti

Zdroj: Cognitive Neurodynamics; 10/23/2025, Vol. 19 Issue 1, p1-32, 32p

Combining recurrent neural networks with variational mode decomposition and multifractals to predict rainfall time series.

Autori: Zhou, Hai Schertzer, Daniel Tchiguirinskaia, Ioulia

Zdroj: Hydrology & Earth System Sciences; 2025, Vol. 29 Issue 18, p4437-4455, 19p

Beyond Deterministic Forecasts: A Scoping Review of Probabilistic Uncertainty Quantification in Short-to-Seasonal Hydrological Prediction.

Autori: De León Pérez, David Salazar-Galán, Sergio Francés, Félix

Zdroj: Water (20734441); Oct2025, Vol. 17 Issue 20, p2932, 28p

Predmety: HYDROLOGICAL forecasting, MACHINE learning, FORECASTING, MEASUREMENT uncertainty (Statistics), ARTIFICIAL intelligence, WATER management

From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications.

Autori: Gkintoni, Evgenia Aroutzidis, Anthimos Antonopoulou, Hera a ďalší

Zdroj: Brain Sciences (2076-3425); Mar2025, Vol. 15 Issue 3, p220, 74p

Predmety: MACHINE learning, EMOTION recognition, COGNITIVE neuroscience, RECURRENT neural networks, DEEP learning

A novel hybrid architecture for video frame prediction: combining convolutional LSTM and 3D CNN.

Autori: Aravinda, C. V. Al-Shehari, Taher Alsadhan, Nasser A. a ďalší

Zdroj: Journal of Real-Time Image Processing; Jan2025, Vol. 22 Issue 1, p1-18, 18p

Sentiment-Driven Statistical Modelling of Stock Returns over Weekends.

Autori: Kutz, Pablo Kowalski Makarov, Roman N.

Zdroj: Computation; Aug2025, Vol. 13 Issue 8, p201, 36p

Predmety: SENTIMENT analysis, NATURAL language processing, RATE of return on stocks, MACHINE learning, STATISTICAL models, STATISTICAL measurement, BUSINESS journalism

Korporácia: APPLE Inc.

Speech Enhancement: A Review of Different Deep Learning Methods.

Autori: Yechuri, Sivaramakrishna Vanabathina, Sunny Dayal

Zdroj: International Journal of Image & Graphics; May2025, Vol. 25 Issue 3, p1-31, 31p

Two‐stream spatiotemporal networks for skeleton action recognition.

Autori: Wang, Lei Zhang, Jianwei Yang, Shanmin a ďalší

Zdroj: IET Image Processing (Wiley-Blackwell); 9/18/2023, Vol. 17 Issue 11, p3358-3370, 13p

Predmety: HUMAN activity recognition, PATTERN recognition systems, HUMAN behavior

Machine learning in stream and river water temperature modeling: a review and metrics for evaluation.

Autori: Corona, Claudia Rebecca Hogue, Terri Sue

Zdroj: Hydrology & Earth System Sciences; 2025, Vol. 29 Issue 12, p2521-2549, 29p

Hierarchical Representation Learning in Graph Neural Networks With Node Decimation Pooling.

Autori: Bianchi, Filippo Maria Grattarola, Daniele Livi, Lorenzo a ďalší

Zdroj: IEEE Transactions on Neural Networks & Learning Systems; May2022, Vol. 33 Issue 5, p2195-2207, 13p

Predmety: REPRESENTATIONS of graphs, TOPOLOGY, SYMMETRIC matrices, PARALLEL algorithms, CHARTS, diagrams, etc., TASK analysis

On Using AI‐Based Large‐Sample Emulators for Land/Hydrology Model Calibration and Regionalization.

Autori: Tang, Guoqiang Wood, Andrew W. Swenson, Sean

Zdroj: Water Resources Research; Jul2025, Vol. 61 Issue 7, p1-18, 18p

Predmety: HYDROLOGY, HYDROLOGIC models, ARTIFICIAL intelligence, RUNOFF, DEEP learning, REGIONAL planning, CALIBRATION

Geografický termín: UNITED States

Back to recurrent processing at the crossroad of transformers and state-space models.

Autori: Tiezzi, Matteo Casoni, Michele Betti, Alessandro a ďalší

Zdroj: Nature Machine Intelligence; May2025, Vol. 7 Issue 5, p678-688, 11p