Results 81 to 90 of about 10,022,386 (288)
When Biology Meets Medicine: A Perspective on Foundation Models
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu +3 more
wiley +1 more source
Linear Scalarization for Byzantine-robust learning on non-IID data
In this work we study the problem of Byzantine-robust learning when data among clients is heterogeneous. We focus on poisoning attacks targeting the convergence of SGD.
Errami, Latifa, Bergou, El Houcine
core
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica +38 more
wiley +1 more source
Dental anomalies in Pleistocene African hippopotamuses from Olduvai Bed II
Abstract Hippopotamuses are key palaeoenvironmental indicators in African Pleistocene ecosystems due to their ecological dependence on permanent water bodies and their frequent representation in the fossil record. This study examines dental anomalies in Hippopotamus cf. gorgops from several localities in Bed II of Olduvai Gorge (Tanzania), dated to ca.
Darío Fidalgo +4 more
wiley +1 more source
Federated PAC-Bayesian Learning on Non-IID data [PDF]
Existing research has either adapted the Probably Approximately Correct (PAC) Bayesian framework for federated learning (FL) or used information-theoretic PAC-Bayesian bounds while introducing their theorems, but few considering the non-IID challenges in
Zhao, Zihao +3 more
core +1 more source
Non-IID latent variable models [PDF]
University of Technology Sydney. Faculty of Engineering and Information Technology.Latent Variable Model (LVM) is the statistical model that aims to uncover hidden information behind data.
Do, Trong Dinh Thac
core +1 more source
FedCD: Improving Performance in non-IID Federated Learning
Federated learning has been widely applied to enable decentralized devices, which each have their own local data, to learn a shared model. However, learning from real-world data can be challenging, as it is rarely identically and independently distributed (IID) across edge devices (a key assumption for current high-performing and low-bandwidth ...
Kavya Kopparapu, Eric Lin, Jessica Zhao
openaire +2 more sources
Genomic Structural Variations Provide Insights Into Litter Size and Teat Number Traits in Hu Sheep
Here, we conducted whole genome sequencing on 300 Hu sheep with an average depth of 16.51X. Two candidate genes associated with litter size and teat number traits were identified, namely MAST2 and AFDN. ABSTRACT Litter size and the teat number are important economic indicators in sheep production.
Xin Xiang +3 more
wiley +1 more source
B5G networks are envisioned to meet higher spectral efficiencies through advanced transmission technologies. Consequently, it is important to comprehend the typical propagation characteristics of wireless communication medium that experience multipath ...
D. L. Sharini +3 more
doaj +1 more source
Homologous membrane wrapped ZIF‐8 nanoparticles were proposed to improve biocompatibility and targeting ability to neural stem cells (NSCs). ZIF‐8‐SCM NPs exhibit pH responsiveness, thereby generating an intracellular Zn2+ storm to accelerate neural differentiation through calcium and MAPK signaling pathways. Moreover, they promote function recovery in
Jie Wang +11 more
wiley +1 more source

