Results 71 to 80 of about 3,000 (250)

Overcoming catastrophic forgetting with hard attention to the task

CoRR, 2018
Includes appendix.
Serrà Julià, Joan, Surís, Dídac, Miron, Marius, Karatzoglou, Alexandros   +3 more
openaire   +4 more sources

Dynamic, Unconstrained Optimization of Secreted Enzyme Production in Fed‐Batch Fermentation Using Reinforcement Learning

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Reinforcement learning (RL) has been used to control a wide range of dynamic processes, especially ones that are too complex to model well or have stochastic environmental perturbations. Fed‐batch fermentations are subject to changes in starting cell growth rates and process variations that can affect cell growth and secreted target production.
Sai Harish Uthravalli, Sakib Ferdous, J. Michael Hess, Nigel F. Reuel   +3 more
wiley   +1 more source

A multifidelity approach to continual learning for physical systems

Machine Learning: Science and Technology
We introduce a novel continual learning method based on multifidelity deep neural networks. This method learns the correlation between the output of previously trained models and the desired output of the model on the current training dataset, limiting ...
Amanda Howard, Yucheng Fu, Panos Stinis
doaj   +1 more source

Investigating Perceptions of the Eating Disorder Examination‐Questionnaire Among Undergraduate Students: A Qualitative Approach

International Journal of Eating Disorders, EarlyView.
ABSTRACT Objective Quantitative methods that have evaluated the Eating Disorder Examination Questionnaire (EDE‐Q) have found consistent evidence that the original four‐factor structure does not replicate across diverse samples and genders. Emerging evidence in the broader psychology literature shows that qualitative methods can provide nuanced insight ...
Katarina L. Huellemann, Safia Ouédraogo, Janet A. Lydecker, Sarah E. Racine   +3 more
wiley   +1 more source

Inter‐Material Transfer Learning for Accelerated Nanofluid Heat Transfer Prediction: A Machine Learning Approach for Energy Systems

Energy Science &Engineering, EarlyView.
This study presents an inter‐material transfer learning framework for nanofluid heat transfer prediction in energy systems. By leveraging knowledge from Al2O3‐water data, the model accurately predicts hybrid Al2O3‐TiO2 nanofluid performance with only 20 simulations, achieving R2 = 0.985 and reducing computational requirements by 78. ABSTRACT This paper
Soumaya Hadj Salah, Aymen Ochi, Sonia Bezi   +2 more
wiley   +1 more source

“You just want to re‐open our biggest wounds, don't you?”: Homeplace ethnography as (polluted) environmental method

Feminist Anthropology, EarlyView.
Abstract When I was 12, my family told me a story about their community falling apart and coming together, a time when someone tried putting a nuclear facility in their (our?) hometown. Since we moved when I was too young to remember, the story had little significance until I embarked on a “hometown” ethnographic journey for my dissertation.
Chandler L. Classen
wiley   +1 more source

Coping Practices of Small‐ and Medium‐Sized Enterprises Facing Power Asymmetry in Digital Platform Business

Strategic Change, EarlyView.
ABSTRACT Digital platform (DP) enterprises have risen to the top of the global economy by inverting traditional business models. They earn money through matchmaking, transaction facilitation, and efficient orchestration of other stakeholders' resources.
Lukas R. G. Fitz, Jochen Scheeg
wiley   +1 more source

Catastrophic Forgetting in Kolmogorov-Arnold Networks

Proceedings of the AAAI Conference on Artificial Intelligence
Catastrophic forgetting is a longstanding challenge in continual learning, where models lose knowledge from earlier tasks when learning new ones. While various mitigation strategies have been proposed for Multi-Layer Perceptrons (MLPs), recent architectural advances like Kolmogorov-Arnold Networks (KANs) have been suggested to offer intrinsic ...
Mohammad Marufur Rahman, Guanchu Wang, Kaixiong Zhou, Minghan Chen 0001, Fan Yang 0023   +4 more
openaire   +2 more sources

Living with the Unknown: Intolerance of Uncertainty in Parkinson's Disease

Movement Disorders Clinical Practice, EarlyView.
Abstract Background Parkinson's disease (PD) is marked by pervasive uncertainty due to fluctuating motor and non‐motor symptoms, variable treatment response, and an unpredictable clinical course. Intolerance of uncertainty (IU), a tendency to perceive ambiguity as threatening and respond with worry, avoidance, or decisional paralysis, may be ...
Bradley McDaniels, Gregory M. Pontone, Kuhan Pushparatnam, Indu Subramanian   +3 more
wiley   +1 more source

Accelerating Stroke MRI With Diffusion Probabilistic Models Through Large‐Scale Pre‐Training and Target‐Specific Fine‐Tuning

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop a data‐efficient strategy for accelerated MRI reconstruction with Diffusion Probabilistic Generative Models (DPMs) that enables faster scan times in clinical stroke MRI when only limited fully‐sampled data are available. Methods Our simple training strategy first pre‐trains a DPM on a large, diverse collection of publicly ...
Yamin Arefeen, Sidharth Kumar, Steven Warach, Hamidreza Saber, Jonathan Isaac Tamir   +4 more
wiley   +1 more source