Results 71 to 80 of about 5,846,406 (312)

Search for deep graph neural networks

Information Sciences, 2023
Current GNN-oriented NAS methods focus on the search for different layer aggregate components with shallow and simple architectures, which are limited by the 'over-smooth' problem. To further explore the benefits from structural diversity and depth of GNN architectures, we propose a GNN generation pipeline with a novel two-stage search space, which ...
Guosheng Feng, Hongzhi Wang 0001, Chunnan Wang   +2 more
openaire   +2 more sources

Microbiome−host proteostasis crosstalk—An emerging perspective on mechanisms and interventions toward healthy longevity

FEBS Letters, EarlyView.
Proteostasis and the gut microbiota play a key role in shaping host physiology. Microbiota‐derived metabolites, vitamins, and RNA modulate host proteostasis. Findings from model systems, including C. elegans, indicate microbes can either stabilize or disrupt host proteostasis.
Abhishek Anil Dubey, Maria Ermolaeva
wiley   +1 more source

Modelling stem cell differentiation related processes—A practical overview for biologists

FEBS Letters, EarlyView.
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar, Xinqi Yan, Lucas F. Jansen Klomp, Stefano Schivo, Janine N. Post   +4 more
wiley   +1 more source

Towards Proving the Adversarial Robustness of Deep Neural Networks [PDF]

Electronic Proceedings in Theoretical Computer Science, 2017
Autonomous vehicles are highly complex systems, required to function reliably in a wide variety of situations. Manually crafting software controllers for these vehicles is difficult, but there has been some success in using deep neural networks generated
Guy Katz, Clark Barrett, David L. Dill, Kyle Julian, Mykel J. Kochenderfer   +4 more
doaj   +1 more source

Deep Neural Network or Dermatologist? [PDF]

, 2019
Deep learning techniques have proven high accuracy for identifying melanoma in digitised dermoscopic images. A strength is that these methods are not constrained by features that are pre-defined by human semantics. A down-side is that it is difficult to understand the rationale of the model predictions and to identify potential failure modes. This is a
Kyle Young, Gareth Booth, Becks Simpson, Reuben Dutton, Sally Shrapnel   +4 more
openaire   +3 more sources

Deep Neural Networks and PIDE Discretizations

SIAM Journal on Mathematics of Data Science, 2022
In this paper, we propose neural networks that tackle the problems of stability and field-of-view of a Convolutional Neural Network (CNN). As an alternative to increasing the network's depth or width to improve performance, we propose integral-based spatially nonlocal operators which are related to global weighted Laplacian, fractional Laplacian and ...
Bastian Bohn, Michael Griebel, Dinesh Kannan   +2 more
openaire   +3 more sources

Microbiome‐blood–brain barrier interactions in aging — mechanisms and therapeutic potential

FEBS Letters, EarlyView.
Aging reshapes the gut microbiome (↓SCFA‐producing commensals; ↑pro‐inflammatory outputs), shifting circulating metabolites (↓SCFAs; ↑LPS, ↑TMAO, ↑PAA) that act at the BBB to increase nonspecific transcytosis, alter transport, and promote astrocyte reactivity, heightening brain vulnerability.
Daniel Cuervo‐Zanatta, Hari Baskar Balasubramanian, Amir Pasokh, Marietta Zille   +3 more
wiley   +1 more source

Error Bounds for Approximations Using Multichannel Deep Convolutional Neural Networks with Downsampling

Journal of Applied Mathematics, 2023
Deep learning with specific network topologies has been successfully applied in many fields. However, what is primarily called into question by people is its lack of theoretical foundation investigations, especially for structured neural networks.
Xinling Liu, Jingyao Hou
doaj   +1 more source

Machine learning methods as an aid in planning orthodontic treatment on the example of Cone-Beam Computed Tomography analysis: a literature review

Journal of Education, Health and Sport, 2021
Convolutional neural networks (CNNs) are used in many areas of computer vision, such as object tracking and recognition, security, military, and biomedical image analysis.
Szymon Płotka, Tomasz Włodarczyk, Ryszard Szczerba, Anna Chomiak, Oskar Komisarek   +4 more
doaj   +1 more source

Epigenetic reprogramming of lineage switching in cancer

FEBS Letters, EarlyView.
Cancer cells rarely commit to a single identity. Epigenetic mechanisms and tumor microenvironment cues push epithelial cells toward flexible, hybrid states that can shift into mesenchymal, neuroendocrine, or stem‐like fates, driving metastasis, drug resistance, and tumor heterogeneity. Targeting the epigenetic regulators behind these transitions, using
Ezgi Boyvatlı, Burcu Akman, Ezgi Bağırsakçı, Nese Atabey, Serap Erkek‐Ozhan   +4 more
wiley   +1 more source