Results 101 to 110 of about 575,581 (334)
This study presents a multitask strategy for plastic cleanup with autonomous surface vehicles, combining exploration and cleaning phases. A two‐headed Deep Q‐Network shared by all agents is traineded via multiobjective reinforcement learning, producing a Pareto front of trade‐offs.
Dame Seck +4 more
wiley +1 more source
Background. One of the directions for solving the problem of increasing the adequacy of mathematical models of processes for ensuring anti-virus protection in computer systems (CS) is the formalization of these processes using the methodological ...
R.A. Khvorov +3 more
doaj +1 more source
The polymerase chain reaction (PCR).Perturbation Theory and Machine Learning framework integrates perturbation theory and machine learning to classify genetic sequences, distinguishing ancient DNA from modern controls and predicting tree health from soil metagenomic data.
Jose L. Rodriguez +19 more
wiley +1 more source
Convergence of option rewards for Markov type price processes modulated by stochastic indices. II [PDF]
Dmitrii Silvestrov +2 more
openalex +1 more source
Correction to: Random Coefficient Autoregressive Processes: a Markov Chain Analysis of Stationarity and Finiteness of Moments by Paul D. Feigin and Richard L. Tweedie J. Time Series Anal., Vol. 6, No. 1 (1985) [PDF]
Paul D. Feigin
openalex +1 more source
General Law of iterated logarithm for Markov processes: Liminf laws [PDF]
Soobin Cho, Panki Kim, Jaehun Lee
openalex +1 more source
gnSPADE integrates gene‐network structures into a probabilistic topic modeling framework to achieve reference‐free cell‐type deconvolution in spatial transcriptomics. By embedding gene connectivity within the generative process, gnSPADE enhances biological interpretability and accuracy across simulated and real datasets, revealing spatial organization ...
Aoqi Xie, Yuehua Cui
wiley +1 more source
A likelihood ratio test for stationarity of rating transitions [PDF]
For a time-continuous discrete-state Markov process as model for rating transitions, we study the time-stationarity by means of a likelihood ratio test. For multiple Markov process data from a multiplicative intensity model, maximum likelihood parameter ...
Walter, Ronja, Weißbach, Rafael
core
Feature Disentangling and Combination Implemented by Spin–Orbit Torque Magnetic Tunnel Junctions
Spin–orbit torque magnetic tunnel junctions (SOT‐MTJs) enable efficient feature disentangling and integration in image data. A proposed algorithm leverages SOT‐MTJs as true random number generators to disentangle and recombine features in real time, with experimental validation on emoji and facial datasets.
Xiaohan Li +15 more
wiley +1 more source
Markov processes on Riesz spaces [PDF]
Jessica J. Vardy, Bruce A. Watson
openalex +1 more source

