162 citations · 840 across the 63 of their papers we have counts for
71 papers
Split Conformal Prediction under Data Contamination
Jase Clarkson, Wenkai Xu, Mihai Cucuringu +2
Conformal prediction is a non-parametric technique for constructing prediction intervals or sets from arbitrary predictive models under the assumption that the data is exchangeable…
SteinGen: Generating Fidelitous and Diverse Graph Samples
Gesine Reinert, Wenkai Xu
Generating graphs that preserve characteristic structures while promoting sample diversity can be challenging, especially when the number of graph observations is small. Here, we t…
L2G2G: a Scalable Local-to-Global Network Embedding with Graph Autoencoders
Ruikang Ouyang, Andrew Elliott, Stratis Limnios +2
For analysing real-world networks, graph representation learning is a popular tool. These methods, such as a graph autoencoder (GAE), typically rely on low-dimensional representati…
Generalization Error of Graph Neural Networks in the Mean-field Regime
Gholamali Aminian, Yixuan He, Gesine Reinert +2
This work provides a theoretical framework for assessing the generalization error of graph neural networks in the over-parameterized regime, where the number of parameters surpasse…
Robust Angular Synchronization via Directed Graph Neural Networks
Yixuan He, Gesine Reinert, David Wipf +1
The angular synchronization problem aims to accurately estimate (up to a constant additive phase) a set of unknown angles from noisy measurements of…
Goodness-of-fit via Count Statistics in Dense Random Simplicial Complexes
Tadas Temčinas, Vidit Nanda, Gesine Reinert
A key object of study in stochastic topology is a random simplicial complex. In this work we study a multi-parameter random simplicial complex model, where the probability of inclu…