Bayesian Graph Neural Networks with Adaptive Connection Sampling

Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki +4

On Sampling from Massive Graph Streams

Nesreen K. Ahmed, Nick Duffield, Theodore Willke +1

Efficient Sampling for Better OSN Data Provisioning

Nick Duffield, Balachander Krishnamurthy

Bayesian Graph Contrastive Learning

Arman Hasanzadeh, Mohammadreza Armandpour, Ehsan Hajiramezanali +3

Signature inversion for monotone paths

Jiawei Chang, Nick Duffield, Hao Ni +1

MoReL: Multi-omics Relational Learning

Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield +1

Graph Sample and Hold: A Framework for Big-Graph Analytics

Nesreen K. Ahmed, Nick Duffield, Jennifer Neville +1

Sampling for Approximate Bipartite Network Projection

Nesreen K. Ahmed, Nick Duffield, Liangzhen Xia

Semi-Implicit Graph Variational Auto-Encoders

Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield +3

Spectral Convolutional Conditional Neural Processes

Peiman Mohseni, Nick Duffield

Graphlet Decomposition: Framework, Algorithms, and Applications

Nesreen K. Ahmed, Jennifer Neville, Ryan A. Rossi +2

InvarGC: Invariant Granger Causality for Heterogeneous Interventional Time Series under Latent Confounding

Ziyi Zhang, Shaogang Ren, Xiaoning Qian +1

Stream Aggregation Through Order Sampling

Nick Duffield, Yunhong Xu, Liangzhen Xia +2

Adaptive Conditional Quantile Neural Processes

Peiman Mohseni, Nick Duffield, Bani Mallick +1

Graph Reconstruction from Path Correlation Data

Gregory Berkolaiko, Nick Duffield, Mahmood Ettehad +1

On the Tradeoff between Stability and Fit

Edith Cohen, Graham Cormode, Nick Duffield +1

Optimizing Consistent Merging and Pruning of Subgraphs in Network Tomography

Mahmood Ettehad, Nick Duffield, Gregory Berkolaiko

Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data

Ziyi Zhang, Shaogang Ren, Xiaoning Qian +1

Towards Invariant Time Series Forecasting in Smart Cities

Ziyi Zhang, Shaogang Ren, Xiaoning Qian +1

BayReL: Bayesian Relational Learning for Multi-omics Data Integration

Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield +2

Variational Graph Recurrent Neural Networks

Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield +3

Tiresias: Online Anomaly Detection for Hierarchical Operational Network Data

Chi-Yao Hong, Matthew Caesar, Nick Duffield +1

Semi-Implicit Stochastic Recurrent Neural Networks

Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield +3

Piecewise Stationary Modeling of Random Processes Over Graphs With an Application to Traffic Prediction

Arman Hasanzadeh, Xi Liu, Nick Duffield +1

Streaming Network Embedding through Local Actions

Xi Liu, Ping-Chun Hsieh, Nick Duffield +3

Sampling to estimate arbitrary subset sums

Nick Duffield, Carsten Lund, Mikkel Thorup

A Semi-Supervised and Inductive Embedding Model for Churn Prediction of Large-Scale Mobile Games

Xi Liu, Muhe Xie, Xidao Wen +4

Near-Optimal Disjoint-Path Facility Location Through Set Cover by Pairs

David S. Johnson, Lee Breslau, Ilias Diakonikolas +6

Revealing the Global Linguistic and Geographical Disparities of Public Awareness to Covid-19 Outbreak through Social Media

Binbin Lin, Lei Zou, Nick Duffield +7

Adaptive Shrinkage Estimation for Streaming Graphs

Nesreen K. Ahmed, Nick Duffield

Micro- and Macro-Level Churn Analysis of Large-Scale Mobile Games

Xi Liu, Muhe Xie, Xidao Wen +4

Revisiting Neural Processes via Fourier Transform and Volterra Series

Peiman Mohseni, Nick Duffield, Raymond K. W. Wong

The paper introduces translation‑equivariant neural processes that use a Volterra series expansion and set Fourier convolutions to model irregularly sampled data with analytical tr…

Temporal Network Sampling

Nesreen K. Ahmed, Nick Duffield, Ryan A. Rossi

Stream sampling for variance-optimal estimation of subset sums

Edith Cohen, Nick Duffield, Haim Kaplan +2

Structure-Aware Sampling: Flexible and Accurate Summarization

Edith Cohen, Graham Cormode, Nick Duffield