Results 31 to 40 of about 122,529 (265)

Wasserstein GAN

CoRR, 2017
We introduce a new algorithm named WGAN, an alternative to traditional GAN training. In this new model, we show that we can improve the stability of learning, get rid of problems like mode collapse, and provide meaningful learning curves useful for debugging and hyperparameter searches.
Martín Arjovsky, Soumith Chintala, Léon Bottou   +2 more
openaire   +2 more sources

Hamiltonian GAN

CoRR, 2023
A growing body of work leverages the Hamiltonian formalism as an inductive bias for physically plausible neural network based video generation. The structure of the Hamiltonian ensures conservation of a learned quantity (e.g., energy) and imposes a phase-space interpretation on the low-dimensional manifold underlying the input video.
openaire   +3 more sources

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source

The Numerics of GANs

CoRR, 2017
In this paper, we analyze the numerics of common algorithms for training Generative Adversarial Networks (GANs). Using the formalism of smooth two-player games we analyze the associated gradient vector field of GAN training objectives. Our findings suggest that the convergence of current algorithms suffers due to two factors: i) presence of eigenvalues
Mescheder, L., Nowozin, S., Geiger, A.
openaire   +4 more sources

Prb-GAN: A Probabilistic Framework for GAN Modelling

CoRR, 2021
Generative adversarial networks (GANs) are very popular to generate realistic images, but they often suffer from the training instability issues and the phenomenon of mode loss. In order to attain greater diversity in GAN synthesized data, it is critical to solving the problem of mode loss.
Blessen George, Vinod K. Kurmi, Vinay P. Namboodiri   +2 more
openaire   +2 more sources

Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig, Nadav Amir, Maya Schiller, Roni Loebenstein, Johnatan Nissan, Marina Boxer, Shany Guly Gofrit, Gal Goshen, Sándor Beniczky, Nicola Maggio   +9 more
wiley   +1 more source

Adaptive Contrast Enhancement for Digital Radiographic Images using Image-to-Image Translation

Current Directions in Biomedical Engineering
Digital radiography in medicine is a widely used imaging method for obtaining visual information about the inside of a body. To prepare the acquired raw image for diagnostic evaluation, the contrast must be adjusted depending on the examined part of the ...
Popp Ann-Kathrin, Schumacher Mona, Himstedt Marian   +2 more
doaj   +1 more source

Growth condition dependence of unintentional oxygen incorporation in epitaxial GaN

Science and Technology of Advanced Materials, 2016
Growth conditions have a tremendous impact on the unintentional background impurity concentration in gallium nitride (GaN) synthesized by molecular beam epitaxy and its resulting chemical and physical properties.
Felix Schubert, Steffen Wirth, Friederike Zimmermann, Johannes Heitmann, Thomas Mikolajick, Stefan Schmult   +5 more
doaj   +1 more source

Federated split GANs

Proceedings of the 1st ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network, 2022
Mobile devices and the immense amount and variety of data they generate are key enablers of machine learning (ML)-based applications. Traditional ML techniques have shifted toward new paradigms such as federated (FL) and split learning (SL) to improve the protection of user's data privacy. However, these paradigms often rely on server(s) located in the
Pranvera Kortoçi, Yilei Liang, Pengyuan Zhou, Lik-Hang Lee, Abbas Mehrabi, Pan Hui 0001, Sasu Tarkoma, Jon Crowcroft   +7 more
openaire   +2 more sources

Re‐Purposing Sapropterin (Kuvan) for ACTA2‐Related Multisystemic Smooth Muscle Dysfunction Syndrome: A Translational Mechanistic and First‐In‐Human Therapeutic Report

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Multisystemic smooth muscle dysfunction syndrome (MSMDS) is an ultra‐rare, ACTA2‐related disorder characterized by severe cerebrovascular disease, aortic aneurysms, and smooth muscle dysfunction. Using molecular dynamics simulations and in silico drug screening, we identified that sapropterin dihydrochloride (Kuvan) is a candidate capable of ...
Moran Hausman‐Kedem, Noa Bielopolski, Vijai Krishnan, Shane Wald‐Altman, Shelly I Shrian, Omer Bar‐Yosef, Livia Kapusta, Claire Shamber, Patricia L. Musolino, Miguel Weil   +9 more
wiley   +1 more source