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08/01/2023
Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects
We present a novel methodology for modeling and forecasting multivariate...
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06/29/2023
SaGess: Sampling Graph Denoising Diffusion Model for Scalable Graph Generation
Over recent years, denoising diffusion generative models have come to be...
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05/25/2023
The GNAR-edge model: A network autoregressive model for networks with time-varying edge weights
In economic and financial applications, there is often the need for anal...
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05/11/2023
Robust Detection of Lead-Lag Relationships in Lagged Multi-Factor Models
In multivariate time series systems, key insights can be obtained by dis...
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04/08/2023
OFTER: An Online Pipeline for Time Series Forecasting
We introduce OFTER, a time series forecasting pipeline tailored for mid-...
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12/01/2022
Symphony in the Latent Space: Provably Integrating High-dimensional Techniques with Non-linear Machine Learning Models
This paper revisits building machine learning algorithms that involve in...
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09/01/2022
MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian
Signed and directed networks are ubiquitous in real-world applications. ...
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03/29/2022
Graph similarity learning for change-point detection in dynamic networks
Dynamic networks are ubiquitous for modelling sequential graph-structure...
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03/28/2022
DAMNETS: A Deep Autoregressive Model for Generating Markovian Network Time Series
In this work, we introduce DAMNETS, a deep generative model for Markovia...
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02/22/2022
PyTorch Geometric Signed Directed: A Survey and Software on Graph Neural Networks for Signed and Directed Graphs
Signed networks are ubiquitous in many real-world applications (e.g., so...
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02/01/2022
GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks
Recovering global rankings from pairwise comparisons is an important pro...
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01/23/2022
Option Volume Imbalance as a predictor for equity market returns
We investigate the use of the normalized imbalance between option volume...
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01/20/2022
Lead-lag detection and network clustering for multivariate time series with an application to the US equity market
In multivariate time series systems, it has been observed that certain g...
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01/12/2022
Local2Global: A distributed approach for scaling representation learning on graphs
We propose a decentralised "local2global"' approach to graph representat...
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10/13/2021
SSSNET: Semi-Supervised Signed Network Clustering
Node embeddings are a powerful tool in the analysis of networks; yet, th...
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07/26/2021
Local2Global: Scaling global representation learning on graphs via local training
We propose a decentralised "local2global" approach to graph representati...
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07/02/2021
DUKweb: Diachronic word representations from the UK Web Archive corpus
Lexical semantic change (detecting shifts in the meaning and usage of wo...
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06/09/2021
DIGRAC: Digraph Clustering with Flow Imbalance
Node clustering is a powerful tool in the analysis of networks. Here, we...
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12/29/2020
An extension of the angular synchronization problem to the heterogeneous setting
Given an undirected measurement graph G = ([n], E), the classical angula...
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11/03/2020
Regularized spectral methods for clustering signed networks
We study the problem of k-way clustering in signed graphs. Considerable ...
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09/23/2020
A Linear Transportation L^p Distance for Pattern Recognition
The transportation L^p distance, denoted TL^p, has been proposed as a ge...
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05/08/2020
Spectral Ranking with Covariates
We consider approaches to the classical problem of establishing a statis...
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04/04/2020
Learning with Semi-Definite Programming: new statistical bounds based on fixed point analysis and excess risk curvature
Many statistical learning problems have recently been shown to be amenab...
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04/02/2020
Motif-Based Spectral Clustering of Weighted Directed Networks
Clustering is an essential technique for network analysis, with applicat...
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12/02/2019
Core-Periphery Structure in Directed Networks
While studies of meso-scale structures in networks often focus on commun...
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09/07/2019
A Deep Learning Framework for Pricing Financial Instruments
We propose an integrated deep learning architecture for the stock moveme...
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08/06/2019
Hermitian matrices for clustering directed graphs: insights and applications
Graph clustering is a basic technique in machine learning, and has wides...
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06/06/2019
Ranking and synchronization from pairwise measurements via SVD
Given a measurement graph G= (V,E) and an unknown signal r ∈R^n, we inve...
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04/18/2019
SPONGE: A generalized eigenproblem for clustering signed networks
We introduce a principled and theoretically sound spectral method for k-...
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01/10/2019
An MBO scheme for clustering and semi-supervised clustering of signed networks
We introduce a principled method for the signed clustering problem, wher...
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01/02/2019
Anomaly Detection in Networks with Application to Financial Transaction Networks
This paper is motivated by the task of detecting anomalies in networks o...
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07/04/2018
Modeling outcomes of soccer matches
We compare various extensions of the Bradley-Terry model and a hierarchi...
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03/09/2018
Provably robust estimation of modulo 1 samples of a smooth function with applications to phase unwrapping
Consider an unknown smooth function f: [0,1]^d →R, and say we are given ...
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10/27/2017
On denoising modulo 1 samples of a function
Consider an unknown smooth function f: [0,1] →R, and say we are given n ...
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04/05/2015
Sync-Rank: Robust Ranking, Constrained Ranking and Rank Aggregation via Eigenvector and Semidefinite Programming Synchronization
We consider the classic problem of establishing a statistical ranking of...
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04/03/2015
Point Localization and Density Estimation from Ordinal kNN graphs using Synchronization
We consider the problem of embedding unweighted, directed k-nearest neig...
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11/02/2011
