Graphical representations model complex networks by encoding entities as vertices and interactions as edges, with recurring subgraphs—or motifs—revealing fundamental organizational principles. We ...
In our initial research phase, Omar Tazi and I established a probabilistic forecasting framework, utilizing Bayesian Networks to map dependencies between oil price movements and key macroeconomic ...
The EM algorithm is based on Yu (2010) (Section 3.1, 2.2.1 & 2.2.2), while the Viterbi algorithm is based on Benouareth et al. (2008).
Single-cell methods are beginning to reveal the intrinsic heterogeneity in cell populations, arising from the interplay of deterministic and stochastic processes. However, it remains challenging to ...
Technology to restore the ability to communicate in paralyzed persons who cannot speak has the potential to improve autonomy and quality of life. An approach that decodes words and sentences directly ...
Accurate target detection and association are vital for the development of reliable target tracking, especially for cell tracking based on microscopy images due to the similarity of cells. We propose ...
In recent years, the accuracy of speech recognition (SR) has been one of the most active areas of research. Despite that SR systems are working reasonably well in quiet conditions, they still suffer ...
Hidden Markov models (HMMs) are a formal foundation for making probabilistic models of linear sequence 'labeling' problems 1,2. They provide a conceptual toolkit for building complex models just by ...
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