Results 61 to 70 of about 184,437 (258)
Modeling Local Search Metaheuristics Using Markov Decision Processes
Local search metaheuristics like tabu search or simulated annealing are popular heuristic optimization algorithms for finding near-optimal solutions for combinatorial optimization problems.
Rubén Ruiz-Torrubiano +3 more
doaj +1 more source
Identifying Cytokine Motif‐Containing, Immunomodulatory Bacterial Proteins in Human Gut Microbiome
By building and constructing HMM (Upper left, blue), the authors identify CMCPs in bacteria genomes and CRC related metagenomes and enriched CRC‐related CMCPs (Upper right, blue). They analyze sequence and structural similarity of hits (Lower left, green), test function with engineered EcN delivered to tumors in a mouse tumor model (Lower right, pink ...
Ziyu Wang +12 more
wiley +1 more source
Learning policies for Markov decision processes from data [PDF]
We consider the problem of learning a policy for a Markov decision process consistent with data captured on the state-actions pairs followed by the policy.
Hanawal, Manjesh K. +3 more
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SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics
ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao +11 more
wiley +1 more source
Portfolio allocation under the vendor managed inventory: A Markov decision process
Markov decision processes have been applied in solving a wide range of optimization problems over the years. This study provides a review of Markov decision processes and investigates its suitability for solutions to portfolio allocation problems under ...
VO Ezugwu, LI Igbinosun
doaj +1 more source
Protein complexes like KIBRA‐PKMζ are crucial for maintaining memories, forming month‐long protein traces in memory‐tagged neurons, but conventional RNA‐seq analysis fails to detect their transcript changes, leaving memory molecules undetected in the shadows of abundantly‐expressed genes.
Jiyeon Han +10 more
wiley +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
MGDP: Mastering a Generalized Depth Perception Model for Quadruped Locomotion
ABSTRACT Perception‐based Deep Reinforcement Learning (DRL) controllers demonstrate impressive performance on challenging terrains. However, existing controllers still face core limitations, struggling to achieve both terrain generality and platform transferability, and are constrained by high computational overhead and sensitivity to sensor noise.
Yinzhao Dong +9 more
wiley +1 more source
A Bayesian framework based on partially observable Markov decision processes (POMDPs) not only predicts subjects’ confidence in a perceptual decision making task but also explains well-known discrepancies between confidence and choice accuracy as arising
Koosha Khalvati +2 more
doaj +1 more source
Ultra‐Wide‐Field Noninvasive Imaging Through Scattering Media Via Physics‐Guided Deep Learning
We propose a physics‐guided adaptive dual‐domain learning method for ultra‐wide‐field noninvasive imaging through scattering media, namely UNI‐Net. Our method not only reduces the requirement for real experimental data by an order of magnitude but also enables clear imaging of complex scenes with an ultra‐large field of view, which is 164 times the OME
Lintao Peng +5 more
wiley +1 more source

