Title: Using Mutual Information of Hypergraph Compressions for Clustering Abstract: Hypergraphs are often used to represent higher order observed relationships between subjects of study. In particular, the vertices of a […]
Title:Geometric Scattering on Measure Spaces Abstract: Geometric Deep Learning is an emerging field of research that aims to extend the success of convolutional neural networks (CNNs) to data with non-Euclidean […]
Title: Identification of the order of semilinear subdiffusion with memory Abstract: See attached abstract
Title:Inferring birth and death rates from population size time series data Abstract: Models of population dynamics are usually formulated and analyzed with net growth rates. However, separately identifying birth and death rates is significant in various biological applications such as disambiguating (1) exploitation vs. interference competition in ecology, (2) bacteriostatic vs. bactericidal antibiotics in clinical […]
Title: A common pathway to cancer: oncogenic mutations abolish p53 oscillations. Abstract: The tumor suppressor p53 oscillates in response to DNA double-strand breaks, a behavior that has been suggested to be essential to its anti-cancer function. Nearly all human cancers have genetic alterations in the p53 pathway; a number of these alterations have been shown to […]
Title: PLSS: A Projected Linear Systems Solver (joint work with Michael Saunders) Abstract: Iteratively solving linear systems has proven to be useful for many large applications. Projection methods use sketching […]
Title: Modeling size distributions and collisions in cloud microphysics Abstract: Feedbacks between a warming atmosphere, emission of aerosols, and clouds and precipitation are one of the most difficult aspects for […]
Title: Towards Understanding the Success of First Order Methods in Training Mildly Overparameterized Networks Abstract: For most problems of interest the loss landscape of a neural network is non-convex and contains a plethora of spurious critical points. Despite this first order methods such as SGD and Adam are in practice remarkably successful at finding optimal, […]
Title: Understanding SARS-CoV-2 viral rebounds with and without treatments. Abstract: In most instances, the characteristics of SARS-CoV-2 mirror the patterns of an acute infection, with viral load rapidly peaking around 5 days post-infection and subsequently clearing within 2 weeks. However, some individuals show signs of viral recrudescence of up to 10000 viral RNA copies/mL shortly […]
Title: The Hartman-Watson distribution: numerical evaluation and applications in mathematical finance Abstract: The Hartman-Watson distribution appears in several problems of applied probability and financial mathematics. Most notably, it determines the […]
Title: Recalibration of Predicted Probabilities Using the "Logit Shift": Why Does It Work, and When Can It Be Expected to Work Well? Abstract: In the context of election analysis, researchers […]
Title Control algorithms for unmanned underwater vehicles: new approaches based on Hamilton-Jacobi equations and reinforcement learning. Abstract Unmanned underwater vehicles (UUVs) are defined by their ability to operate without direct human intervention. As a result, UUVs are valuable for surveillance tasks, especially in the presence of hazardous environmental conditions. Specific applications of UUVs include seafloor mapping, […]
