We consider the problem of steering an initial probability density for the state vector of a linear
system to a final one, in finite time, using minimum energy control. In the case where the …

Neuroblastoma accounts for 15% of pediatric cancer deaths, and although a few protein-coding
genes, such as MYCN, are involved with aggressive pathogenicity, the identification of …

We introduce an optimal mass transport framework on the space of Gaussian mixture models.
These models are widely used in statistical inference. Specifically, we treat the Gaussian …

The past few years have witnessed the great success of Diffusion models~(DMs) in generating
high-fidelity samples in generative modeling tasks. A major limitation of the DM is its …

Background MicroRNAs (miRNAs) have critical functions in various biological processes.
MiRNA profiling is an important tool for the identification of differentially expressed miRNAs in …

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide.
Several studies have identified signature gene sets that may be useful as potential diagnostic …

We take a new look at the relation between the optimal transport problem and the
Schrödinger bridge problem from a stochastic control perspective. Our aim is to highlight new …

We consider the problem of steering a linear dynamical system with complete state observation
from an initial Gaussian distribution in state-space to a final one with minimum energy …

Hyaluronic acid (HA)-based antioxidant hydrogels have achieved remarkable results in diabetic
wound repair. However, the realization of their glucose-responsive antioxidant functions …

We consider guiding denoising diffusion models with general differentiable loss functions in
a plug-and-play fashion, enabling controllable generation without additional training. This …