output
20142026
most citedFederated Learning Enables Big Data for Rare Cancer Boundary Detection

390 citations

Showing 2022Show all

7 papers · 1 filter

eess.SP2022★ 6 cited

Real-time rapid leakage estimation for deep space habitats using exponentially-weighted adaptively-refined search

Mahindra Rautela, Motahareh Mirfarah, Christian Silva +3

The recent accelerated growth in space-related research and development activities makes the near-term need for long-term extraterrestrial habitats evident. Such habitats must oper…

physics.chem-ph2022★ 9 cited

Photo-accelerated water dissociation across one-atom-thick electrodes

J. Cai, E. Griffin, V. Guarochico-Moreira +6

Recent experiments demonstrated that interfacial water dissociation (H2O = H+ + OH-) could be accelerated exponentially by an electric field applied to graphene electrodes, a pheno…

cs.RO2022★ 15 cited

A sensor-to-pattern calibration framework for multi-modal industrial collaborative cells

Daniela Rato, Miguel Oliveira, Vítor Santos +2

Collaborative robotic industrial cells are workspaces where robots collaborate with human operators. In this context, safety is paramount, and for that a complete perception of the…

physics.chem-ph2022★ 49 cited

Wien effect in interfacial water dissociation through proton-permeable graphene electrodes

J. Cai, E. Griffin, V. Guarochico-Moreira +7

Strong electric fields can accelerate molecular dissociation reactions. The phenomenon known as the Wien effect was previously observed using high-voltage electrolysis cells that p…

math.DG2022★ 3 cited

Geometric and analytic results for Einstein solitons

Enrique Fernando López Agila, José Nazareno Vieira Gomes

We compute a lower bound for the scalar curvature of a gradient Einstein soliton under a certain assumption on its potential function. We establish an asymptotic behavior of the po…

cs.LG2022★ 390 cited

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Sarthak Pati, Ujjwal Baid, Brandon Edwards +276

Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…

cond-mat.soft2022★ 1 cited

Understanding Brownian yet non-Gaussian diffusion via long-range molecular interactions

Francisco E. Alban Chacón, Erick A. Lamilla Rubio, Manuel S. Alvarez Alvarado

In the last years, a few experiments in the fields of biological and soft matter physics in colloidal suspensions have reported normal diffusion with a Laplacian probability distri…