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This paper introduces a systematic approach to address the topological path identification (TPI) problem in power distribution networks. Our approach starts by listing the DSO's raw information coming from several sources. The raw…

Systems and Control · Electrical Eng. & Systems 2024-09-17 Maurizio Vassallo , Alireza Bahmanyar , Laurine Duchesne , Adrien Leerschool , Simon Gerard , Thomas Wehenkel , Damien Ernst

An acoustic topological insulator (TI) is synthesized using topology optimization, a free material inverse design method. The TI appears spontaneously from the optimization process without imposing requirements on the existence of pseudo…

Mesoscale and Nanoscale Physics · Physics 2019-06-19 Rasmus E. Christiansen , Fengwen Wang , Ole Sigmund

We introduce the Stellar decomposition, a model for efficient topological data structures over a broad range of simplicial and cell complexes. A Stellar decomposition of a complex is a collection of regions indexing the complex's vertices…

Data Structures and Algorithms · Computer Science 2021-08-05 Riccardo Fellegara , Kenneth Weiss , Leila De Floriani

Summarizing topological information from datasets and maps defined on them is a central theme in topological data analysis. \textsf{Mapper}, a tool for such summarization, takes as input both a possibly high dimensional dataset and a map…

Computational Geometry · Computer Science 2016-01-13 Tamal K. Dey , Facundo Memoli , Yusu Wang

Given two boundary distributions, the Schr\"odinger Bridge (SB) problem seeks the ``most likely`` random evolution between them with respect to a reference process. It has revealed rich connections to recent machine learning methods for…

Machine Learning · Computer Science 2025-06-03 Maosheng Yang

In the evolving landscape of sixth-generation (6G) wireless networks, which demand ultra high data rates, this study introduces the concept of super constellation communications. Also, we present super amplitude phase shift keying (SAPSK),…

An important issue with oversampled FIR analysis filter banks (FBs) is to determine inverse synthesis FBs, when they exist. Given any complex oversampled FIR analysis FB, we first provide an algorithm to determine whether there exists an…

Information Theory · Computer Science 2023-01-19 Jerome Gauthier , Laurent Duval , Jean-Christophe Pesquet

This primary purpose of this paper is to succinctly state a number of verifiable and tractable sufficient conditions under which a particular class of conservative signal processing structures may be readily used to solve a companion class…

Numerical Analysis · Computer Science 2015-10-20 Tarek A. Lahlou , Thomas A. Baran

We present an exact formulation of the symmetric Traveling Salesman Problem (TSP) that replaces the classical edge-selection view with a surface-building approach. Instead of selecting edges to form a cycle, the model selects a set of…

General Mathematics · Mathematics 2026-03-03 Yılmaz Arslanoğlu

A filtration over a simplicial complex $K$ is an ordering of the simplices of $K$ such that all prefixes in the ordering are subcomplexes of $K$. Filtrations are at the core of Persistent Homology, a major tool in Topological Data Analysis.…

Computational Geometry · Computer Science 2018-02-06 Jean-Daniel Boissonnat , Karthik C. S.

Compared with the rapid development of single-frequency multi-polarization SAR image classification technology, there is less research on the land cover classification of multifrequency polarimetric SAR (MF-PolSAR) images. In addition, the…

Image and Video Processing · Electrical Eng. & Systems 2023-05-03 Yice Cao , Yan Wu , Ming Li , Mingjie Zheng , Peng Zhang , Jili Wang

Neural manifolds summarize the intrinsic structure of the information encoded by a population of neurons. Advances in experimental techniques have made simultaneous recordings from multiple brain regions increasingly commonplace, raising…

Neurons and Cognition · Quantitative Biology 2025-03-27 Iris H. R. Yoon , Gregory Henselman-Petrusek , Yiyi Yu , Robert Ghrist , Spencer LaVere Smith , Chad Giusti

Machine learning techniques using neural networks have achieved promising success for time-series data classification. However, the models that they produce are challenging to verify and interpret. In this paper, we propose an explainable…

Formal Languages and Automata Theory · Computer Science 2023-07-04 Danyang Li , Mingyu Cai , Cristian-Ioan Vasile , Roberto Tron

We present a topological framework for analysing neural time series that integrates Transfer Entropy (TE) with directed Persistent Homology (PH) to characterize information flow in spiking neural systems. TE quantifies directional influence…

Neurons and Cognition · Quantitative Biology 2025-08-27 Dylan Peek , Siddharth Pritam , Matthew P. Skerritt , Stephan Chalup

Transformer-based models for time series forecasting (TSF) have attracted significant attention in recent years due to their effectiveness and versatility. However, these models often require extensive hyperparameter optimization (HPO) to…

Machine Learning · Computer Science 2025-01-03 Jingjing Xu , Caesar Wu , Yuan-Fang Li , Grégoire Danoy , Pascal Bouvry

Conformal prediction is a framework for predictive inference with a distribution-free, finite-sample guarantee. However, it tends to provide uninformative prediction sets when calibration data are scarce. This paper introduces…

Machine Learning · Computer Science 2025-06-17 Meshi Bashari , Roy Maor Lotan , Yonghoon Lee , Edgar Dobriban , Yaniv Romano

Symmetry-protected topological (SPT) phases exhibit nontrivial order if symmetry is respected but are adiabatically connected to the trivial product phase if symmetry is not respected. However, unlike the symmetry-breaking phase, there is…

Strongly Correlated Electrons · Physics 2016-05-04 Ching-Yu Huang , Tzu-Chieh Wei

We introduce a new "subpixel-smoothed projection" (SSP) formulation for differentiable binarization in topology optimization (TopOpt) as a drop-in replacement for previous projection schemes, which suffer from near-non-differentiability and…

The main result of this thesis is the development of a novel connectivity estimation method, called Total Spiking Probability Edges (TSPE). Based on cross-correlation and edge filtering at different time scales this method is proposed and…

Signal Processing · Electrical Eng. & Systems 2020-05-15 Stefano De Blasi

This thesis develops signal-processing algorithms and implementation schemes under constraints of minimal parallelism and memory space, with the goal of improving energy efficiency of low-power computing hardware. We propose (i) a…

Signal Processing · Electrical Eng. & Systems 2025-12-30 Sergey Salishev