Search Results for author:
Found 8 papers, 3 papers with code
Gradient-flow adaptive importance sampling for Bayesian leave one out cross-validation for sigmoidal classification models
We introduce a set of gradient-flow-guided adaptive importance sampling (IS) transformations to stabilize Monte-Carlo approximations of point-wise leave one out cross-validated (LOO) predictions for Bayesian classification models.
Reliable ligand discrimination in stochastic multistep kinetic proofreading: First passage time vs. product counting strategies
We find that loss of fidelity for longer proofreading steps relies on the specific strategy of information extraction and show that in the first-passage time (FPT) discrimination strategy, longer proofreading steps can exponentially improve the accuracy of KPR at the cost of speed.
Squared Wasserstein-2 Distance for Efficient Reconstruction of Stochastic Differential Equations
We provide an analysis of the squared Wasserstein-2 ($W_2$) distance between two probability distributions associated with two stochastic differential equations (SDEs).
A Spectral Approach for Learning Spatiotemporal Neural Differential Equations
Rapidly developing machine learning methods has stimulated research interest in computationally reconstructing differential equations (DEs) from observational data which may provide additional insight into underlying causative mechanisms.
Stochastic nucleosome disassembly mediated by remodelers and histone fragmentation
The dissociation process can be facilitated by DNA binding proteins or processing molecular motors that compete with histones for histone-DNA contact sites.
The role of APOBEC3-induced mutations in the differential evolution of monkeypox virus
Recent studies show that newly sampled monkeypox virus (MPXV) genomes exhibit mutations consistent with Apolipoprotein B mRNA Editing Catalytic Polypeptide-like3 (APOBEC3)-mediated editing, compared to MPXV genomes collected earlier.
Overcompensation of transient and permanent death rate increases in age-structured models with cannibalistic interactions
There has been renewed interest in understanding the mathematical structure of ecological population models that lead to overcompensation, the process by which a population recovers to a higher level after suffering a permanent increase in predation or harvesting.
Stochastic dynamics and ribosome-RNAP interactions in Transcription-Translation Coupling
Such transcription-translation coupling (TTC) has been evoked as a mechanism that speeds up the overall process, provides protection during the transcription, and/or regulates the timing of transcript and protein formation.
