Seminar

We will discuss about “Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics”, Ji et al., The Journal of Physical Chemistry A, 2020 The recently developed physics-informed neural network (PINN) has achieved success in many science and engineering disciplines by encoding physics laws into the loss functions of the neural network such that the network not …

We will discuss about "Information Integration and Energy Expenditure in Gene Regulation", Estrada et al., Cell, 2016 Abstract: The quantitative concepts used to reason about gene regulation largely derive from bacterial studies. We show that this bacterial paradigm cannot explain the sharp expression of a canonical developmental gene in response to a regulating transcription factor …

We will discuss about "The Generalized Multiset Sampler", Kim and MacEachern, The Journal of Computation and Graphical Statistics, 2021 Abstract: The multiset sampler, an MCMC algorithm recently proposed by Leman and coauthors, is an easy-to-implement algorithm which is especially well-suited to drawing samples from a multimodal distribution. We generalize the algorithm by redefining the multiset …