Results 201 to 210 of about 89,200 (262)
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob +2 more
wiley +1 more source
Composite Biomimetic Multi-Subsoiler for Drag Reduction and Wear Resistance Simulation and Experimental Validation. [PDF]
Wang X +6 more
europepmc +1 more source
Energy-Efficient 3D Trajectory Optimization and Resource Allocation for UAV-Enabled ISAC Systems. [PDF]
Jing L +5 more
europepmc +1 more source
UAV-Assisted Covert Communication with Dual-Mode Stochastic Jamming. [PDF]
Gu M, Su Y, Ma Z, Lian Z, Wang Y.
europepmc +1 more source
Wigner Distribution Sets Universal Lower Bound for Quantum Advantage in Gaussian Boson Sampling. [PDF]
Kocharovsky VV, Kalra K.
europepmc +1 more source
Secrecy Rate Maximization for Movable Antenna-Aided STAR-RIS in Integrated Sensing and Communication Systems. [PDF]
Chen G +6 more
europepmc +1 more source
On Convexity of Cooperative Games (Nonlinear Analysis and Convex Analysis)
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Convex multiresolution analysis
Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96), 1998A standard wavelet multiresolution analysis can be defined via a sequence of projection operators onto a monotone sequence of closed vector subspaces possessing suitable invariance properties. We propose an extension of this framework in which the linear projection operators are replaced by nonlinear retractions onto convex sets.
P.L. Combettes, J.-C. Pesquet
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