This is an introductory reading seminar presented by a senior undergraduate student, Jaehak Lee, who is studying the subject.

Geometric and topological structures can aid statistics in several ways. In high dimensional statistics, geometric structures can be used to reduce dimensionality. High dimensional data entails the curse of dimensionality, which can be avoided if there are low dimensional geometric structures. On the other hand, geometric and topological structures also provide useful information. Structures may carry scientific meaning about the data and can be used as features to enhance supervised or unsupervised learning. In this talk, I will explore how statistical inference can be done on geometric and topological structures. First, given a manifold assumption, I will explore the minimax rate for estimating the dimension of the manifold. Second, also under the manifold assumption, I will explore the minimax rate for estimating the reach, which is a regularity quantity depicting how a manifold is smooth and far from self-intersecting. Third, I will investigate inference on cluster trees, which is a hierarchy tree of high-density clusters of a density function. Fourth, I will investigate inference on persistent homology, which quantifies salient topological features that appear at different resolutions of the data.

"Anti-Windup Protection Circuits for Biomolecular Integral Controllers", bioRxaiv. (2023) will be discussed in this Journal Club. In this study, we obtain an exact time-dependent solution of the chemical master equation (CME) of an extension of the two-state telegraph model describing bursty or non-bursty protein expression in the presence of positive or negative autoregulation. Using the method of spectral decomposition, we show that the eigenfunctions of the generating function solution of the CME are Heun functions, while the eigenvalues can be determined by solving a continued fraction equation. Our solution generalizes and corrects a previous time-dependent solution for the CME of a gene circuit describing non-bursty protein expression in the presence of negative autoregulation [Ramos et al., Phys. Rev. E 83, 062902 (2011)]. In particular, we clarify that the eigenvalues are generally not real as previously claimed. We also investigate the relationship between different types of dynamic behavior and the type of feedback, the protein burst size, and the gene switching rate. If you want to participate in the seminar, you need to enter IBS builiding (https://www.ibs.re.kr/bimag/visiting/). Please contact if you first come IBS to get permission to enter IBS building.

For hyperbolic manifolds, many interesting results support a deep relationship between hyperbolic volume and the Chern-Simons invariant. In this talk, we consider noncompact hyperbolic 3-manifolds having infinite volume. For these manifolds, there is a well-defined invariant called the renormalized volume which replaces classical volume. The talk will start from a gentle introduction to hyperbolic geometry and reach the renormalization of the Chern-Simons invariant, which has a close relationship with the renormalized hyperbolic volume.

In this talk, I will discuss recent results on the free energy of logarithmically interacting charges in the plane in an external field. Specifically, at a particular inverse temperature $\beta=2$, this system exhibits the distribution of eigenvalues of certain random matrices, forming a determinantal point process. I will explain how the large N expansion of the free energy depends on the geometric and topological properties of the region where particles condensate, considering the disk, annulus, and sphere cases. I will further discuss the conditional Ginibre ensemble as a non-radial example confirming the Zabrodin-Wiegmann conjecture regarding the spectral determinant emerging at the O(1) term in the free energy expansion. This talk is based on joint works with Sung-Soo Byun, Meng Yang, and  Nam-Gyu Kang.

The Kudla-Rapoport conjecture predicts a relation between the arithmetic intersection numbers of special cycles on a unitary Shimura variety and the derivative of representation densities for hermitian forms at a place of good reduction. In this talk, I will present a variant of the Kudla-Rapoport conjecture at a place of bad reduction. Additionally, I will discuss a proof of the conjecture in several new cases in any dimension. This is joint work with Qiao He and Zhiyu Zhang.

Let $\mathcal{G}$ and $\mathcal{H}$ be minor-closed graphs classes. The class $\mathcal{H}$ has the Erdős-Pósa property in $\mathcal{G}$ if there is a function $f : \mathbb{N} \to \mathbb{N}$ such that every graph $G$ in $\mathcal{G}$ either contains (a packing of) $k$ disjoint copies of some subgraph minimal graph $H \not\in \mathcal{H}$ or contains (a covering of) $f(k)$ vertices, whose removal creates a graph in $\mathcal{H}$. A class $\mathcal{G}$ is a minimal EP-counterexample for $\mathcal{H}$ if $\mathcal{H}$ does not have the Erdős-Pósa property in $\mathcal{G}$, however it does have this property for every minor-closed graph class that is properly contained in $\mathcal{G}$. The set $\frak{C}_{\mathcal{H}}$ of the subset-minimal EP-counterexamples, for every $\mathcal{H}$, can be seen as a way to consider all possible Erdős-Pósa dualities that can be proven for minor-closed classes. We prove that, for every $\mathcal{H}$, $\frak{C}_{\mathcal{H}}$ is finite and we give a complete characterization of it. In particular, we prove that $|\frak{C}_{\mathcal{H}}| = 2^{\operatorname{poly}(\ell(h))}$, where $h$ is the maximum size of a minor-obstruction of $\mathcal{H}$ and $\ell(\cdot)$ is the unique linkage function. As a corollary of this, we obtain a constructive proof of Thomas' conjecture claiming that every minor-closed graph class has the half-integral Erdős-Pósa property in all graphs. This is joint work with Christophe Paul, Dimitrios Thilikos, and Sebastian Wiederrecht.

Scientific knowledge, written in the form of differential equations, plays a vital role in various deep learning fields. In this talk, I will present a graph neural network (GNN) design based on reaction-diffusion equations, which addresses the notorious oversmoothing problem of GNNs. Since the self-attention of Transformers can also be viewed as a special case of graph processing, I will present how we can enhance Transformers in a similar way. I will also introduce a spatiotemporal forecasting model based on neural controlled differential equations (NCDEs). NCDEs were designed to process irregular time series in a continuous manner and for spatiotemporal processing, it needs to be combined with a spatial processing module, i.e., GNN. I will show how this can be done.

This is part of an informal seminar series to be given by Mr. Jaehong Kim, who has been studying the book "Hodge theory and Complex Algebraic Geometry Vol 1 by Claire Voisin" for a few months. There will be 6-8 seminars during Spring 2024, and it will summarize about 70-80% of the book.

“Transcriptome-wide analysis of cell cycle-dependent bursty gene expression from single-cell RNA-seq data using mechanistic model-based inference”, bioRxiv (2024) will be discussed in this Journal Club. Bursty gene expression is quantified by two intuitive parameters: the burst frequency and the burst size. While these parameters are known to be cell-cycle dependent for some genes, a transcriptome-wide picture remains missing. Here we address this question by fitting a suite of mechanistic models of gene expression to mRNA count data for thousands of mouse genes, obtained by sequencing of single cells for which the cell-cycle position has been inferred using a deep-learning approach. This leads to the estimation of the burst frequency and size per allele in the G1 and G2/M cell-cycle phases, hence providing insight into the global patterns of transcriptional regulation. In particular, we identify an interesting balancing mechanism: on average, upon DNA replication, the burst frequency decreases by ≈ 50%, while the burst size increases by the same amount. We also show that for accurate estimation of the ratio of burst parameters in the G1 and G2/M phases, mechanistic models must explicitly account for gene copy number differences between cells but, surprisingly, additional corrections for extrinsic noise due to the coupling of transcription to cell age within the cell cycle or technical noise due to imperfect capture of RNA molecules in sequencing experiments are unnecessary. If you want to participate in the seminar, you need to enter IBS builiding (https://www.ibs.re.kr/bimag/visiting/). Please contact if you first come IBS to get permission to enter IBS building.

In dimension 4, the works of Freedman and Donaldson led us to the striking discovery that the smooth category is drastically different from the topological category, compared to other dimensions. Since then, it has been extraordinarily successful in investigating the difference in various contexts. In contrast, our understanding of when smooth and topological categories would exhibit similarity in dimension 4 remained, at best, minimal. In this talk, we will introduce some recent progress on new “topological = smooth” results in dimension 4, focusing on embedded disks.

Motivated by the Cohen-Lenstra heuristics, Friedman and Washington studied the distribution of the cokernels of random matrices over the ring of p-adic integers. This has been generalized in many directions, as well as some applications to the distribution of random algebraic objects. In this talk, first we give an overview of random matrix theory over the ring of p-adic integers, together with their connections to conjectures in number theory. After that, we investigate the distribution of the cokernels of random p-adic matrices with given zero entries. The second part of this talk is based on work in progress with Gilyoung Cheong, Dong Yeap Kang and Myungjun Yu.

The Julia set of a (hyperbolic) rational map naturally comes embedded in the Riemann sphere, and thus has a Hausdorff dimension. But the Hausdorff dimension varies if we tweak the parameters slightly. Is there a "best" representative or more invariant dimension? One answer comes from looking at quasi-symmetries; the \emph{conformal dimension} of the Julia set is the minimum Hausdorff dimension of any metri quasi-symmetric to the original. We characterize the Ahlfors-regular conformal dimension of Julia sets of rational maps using graphical energies arising from a natural combinatorial description. (Ahlfors-regular is a dynamically natural extra condition on the metric.) This is joint work with Kevin Pilgrim.

This talk presents mathematical modeling, numerical analysis and simulation using finite element method in the field of electromagnetics at various scales, from analyzing quantum mechanical effects to calculating the scattering of electromagnetic wave in free space. First, we discuss and analyze the Schrodinger-Poisson system of quantum transport model to calculate electron states in three-dimensional heterostructures. Second, the electromagnetic vector wave scattering problem is solved to analyze the field characteristics in the presence of stealth platform. This talk also introduces several challenging issues in these applications and proposes their solutions through mathematical analysis.

This is an introductory reading seminar presented by a senior undergraduate student, Jaehak Lee, who is studying the subject.

TBA

A rational map, like f(z) = (1+z^2)/(1-z^2), gives a map from the (extended) complex plane to itself. Studying the dynamics under iteration yields beautiful Julia set fractals with intricate nested structure. How can that structure be best understood? One approach is combinatorial or topological, giving concrete models for the Julia set and tools for cataloguing the possibilities.

Momentum-based acceleration of first-order optimization methods, first introduced by Nesterov, has been foundational to the theory and practice of large-scale optimization and machine learning. However, finding a fundamental understanding of such acceleration remains a long-standing open problem. In the past few years, several new acceleration mechanisms, distinct from Nesterov’s, have been discovered, and the similarities and dissimilarities among these new acceleration phenomena hint at a promising avenue of attack for the open problem. In this talk, we discuss the envisioned goal of developing a mathematical theory unifying the collection of acceleration mechanisms and the challenges that are to be overcome.

"Reduced model for female endocrine dynamics: Validation and functional variations", Mathematical Biosciences (2023) will be discussed in this Journal Club. A normally functioning menstrual cycle requires significant crosstalk between hormones originating in ovarian and brain tissues. Reproductive hormone dysregulation may cause abnormal function and sometimes infertility. The inherent complexity in this endocrine system is a challenge to identifying mechanisms of cycle disruption, particularly given the large number of unknown parameters in existing mathematical models. We develop a new endocrine model to limit model complexity and use simulated distributions of unknown parameters for model analysis. By employing a comprehensive model evaluation, we identify a collection of mechanisms that differentiate normal and abnormal phenotypes. We also discover an intermediate phenotype—displaying relatively normal hormone levels and cycle dynamics—that is grouped statistically with the irregular phenotype. Results provide insight into how clinical symptoms associated with ovulatory disruption may not be detected through hormone measurements alone. If you want to participate in the seminar, you need to enter IBS builiding (https://www.ibs.re.kr/bimag/visiting/). Please contact if you first come IBS to get permission to enter IBS building.

We prove a conjecture of Bonamy, Bousquet, Pilipczuk, Rzążewski, Thomassé, and Walczak, that for every graph $H$, there is a polynomial $p$ such that for every positive integer $s$, every graph of average degree at least $p(s)$ contains either $K_{s,s}$ as a subgraph or contains an induced subdivision of $H$. This improves upon a result of Kühn and Osthus from 2004 who proved it for graphs whose average degree is at least triply exponential in $s$ and a recent result of Du, Girão, Hunter, McCarty and Scott for graphs with average degree at least singly exponential in $s$. As an application, we prove that the class of graphs that do not contain an induced subdivision of $K_{s,t}$ is polynomially $\chi$-bounded. In the case of $K_{2,3}$, this is the class of theta-free graphs, and answers a question of Davies. Along the way, we also answer a recent question of McCarty, by showing that if $\mathcal{G}$ is a hereditary class of graphs for which there is a polynomial $p$ such that every bipartite $K_{s,s}$-free graph in $\mathcal{G}$ has average degree at most $p(s)$, then more generally, there is a polynomial $p'$ such that every $K_{s,s}$-free graph in $\mathcal{G}$ has average degree at most $p'(s)$. Our main new tool is an induced variant of the Kővári-Sós-Turán theorem, which we find to be of independent interest. This is joint work with Romain Bourneuf (ENS de Lyon), Matija Bucić (Princeton), and James Davies (Cambridge),

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ZOOM ID: 997 8258 4700(pw: 1234)

Optimal Transport (OT) problem investigates a transport map that bridges two distributions while minimizing a specified cost function. OT theory has been widely utilized in generative modeling. Initially, the OT-based Wasserstein metric served as a measure for assessing the distance between data and generated distributions. More recently, the OT transport map, connecting data and prior distributions, has emerged as a new approach for generative models. In this talk, we will introduce generative models based on Optimal Transport. Specifically, we will present our work on a generative model utilizing Unbalanced Optimal Transport. We will also discuss our subsequent efforts to address the challenges associated with this approach.

This is part of an informal seminar series to be given by Mr. Jaehong Kim, who has been studying the book "Hodge theory and Complex Algebraic Geometry Vol 1 by Claire Voisin" for a few months. There will be 6-8 seminars during Spring 2024, and it will summarize about 70-80% of the book.

List flow is a geometric flow for a pair $(g,u)$, where $g$ is a Riemannian metric and $u$ a smooth function. This extended Ricci flow system has applications to static vacuum solutions of the Einstein equations and to Ricci flow on warped products. The coupling induces additional difficulties compared to Ricci flow, which we overcome by proving an improved bound on the Hessian of the function u. This allows us to prove a convergence result, a singularity classification result and a surgery result in three dimensions.

There has been a raising interest on the study of perfect matchings in uniform hypergraphs in the past two decades, including extremal problems and their algorithmic versions. I will introduce the problems and some recent developments.

정보 이론의 주요 관심사 중 하나는 통신 과정에서 오류가 발생할 확률을 최소화하는 것이다. 예를 들어 PCR 검사 결과 음성일 경우 0으로 코드화하고 양성일 경우 1로 코드화한다고 하였을 때, 이 중요한 정보가 통신 상황에서 오류가 발생하여 0이 1로 잘못 전달되거나 1이 0으로 잘못 전달되는 경우가 발생할 수 있다. 만약 오류 발생 확률이 10%라면 적절한 방법을 동원하여 오류 발생 확률을 3% 혹은 1% 등으로 줄이기 위해 노력하는 것이 자연스럽다. 강연 전반부의 목표는 주어진 자원의 어느 정도를 오류 정정에 사용하는 것이 가장 효율적일지를 다루는 샤논 채널 코딩 정리의 의미를 이해하는 것이다. 그리고 강연 후반부의 목표는 최근 큰 주목을 받고 있는 양자 정보 이론 분야에서 2000년대 초반 확립된 코딩 정리의 의미를 파악하고, 이와 관련한 수학적 난제를 소개하는 것이다.

We prove the existence of a computable function $f\colon\mathbb{N}\to\mathbb{N}$ such that for every integer $k$ and every digraph $D$ either contains a collection $\mathcal{C}$ of $k$ directed cycles of even length such that no vertex of $D$ belongs to more than four cycles in $\mathcal{C}$, or there exists a set $S\subseteq V(D)$ of size at most $f(k)$ such that $D-S$ has no directed cycle of even length. This is joint work with Maximilian Gorsky, Ken-ichi Kawarabayashi, and Stephan Kreutzer.

Dyson Brownian motion, the eigenvalues of matrix-valued Brownian motion, has become the most standard and well-established approach to universalities for local (i.e. microscopic) eigenvalue statistics of Hermitian random matrices. When combined with a noble characteristic flow method, it can also help study the eigenvalue statistics on a mesoscopic scale. In this talk, we demonstrate this mechanism via yet another simplification of the proof of local laws for Wigner matrices and discuss some generalities.

The uniform Turán density $\pi_u(F)$ of a hypergraph $F$, introduced by Erdős and Sós, is the smallest value of $d$ such that any hypergraph $H$ where all linear-sized subsets of vertices of $H$ have density greater than $d$ contains $F$ as a subgraph. Over the past few years the value of $\pi_u(F)$ was determined for several classes of 3-graphs, but no nonzero value of $\pi_u(F)$ has been found for $r$-graphs with $r>3$. In this talk we show the existence of $r$-graphs $F$ with $\pi_u(F)={r \choose 2}^{-{r \choose 2}}$, which we conjecture is minimum possible. Joint work with Frederik Garbe, Daniel Il’kovic, Dan Král’ and Filip Kučerák.

Cell-to-cell variability in gene expression exists even in a homogeneous population of cells. Dissecting such cellular heterogeneity within a biological system is a prerequisite for understanding how a biological system is developed, homeostatically regulated, and responds to external perturbations. Single-cell RNA sequencing (scRNA-seq) allows the quantitative and unbiased characterization of cellular heterogeneity by providing genome-wide molecular profiles from tens of thousands of individual cells. Single-cell sequencing is expanding to combine genomic, epigenomic, and transcriptomic features with environmental cues from the same single cell. In this talk, I demonstrate how scRNA-seq can be applied to dissect cellular heterogeneity and plasticity of adipose tissue, and discuss related computational challenges.