Davide Mottin | DeepAI

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∙ 09/04/2023

On the Robustness of Post-hoc GNN Explainers to Label Noise

Proposed as a solution to the inherent black-box limitations of graph ne...

0 Zhiqiang Zhong, et al. ∙

∙ 08/29/2023

How Faithful are Self-Explainable GNNs?

Self-explainable deep neural networks are a recent class of models that ...

0 Marc Christiansen, et al. ∙

∙ 05/12/2023

ActUp: Analyzing and Consolidating tSNE and UMAP

tSNE and UMAP are popular dimensionality reduction algorithms due to the...

0 Andrew Draganov, et al. ∙

∙ 02/16/2023

Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to Interpretability

The integration of Artificial Intelligence (AI) into the field of drug d...

13 Zhiqiang Zhong, et al. ∙

∙ 06/20/2022

GiDR-DUN; Gradient Dimensionality Reduction – Differences and Unification

TSNE and UMAP are two of the most popular dimensionality reduction algor...

0 Andrew Draganov, et al. ∙

∙ 06/10/2021

GRASP: Graph Alignment through Spectral Signatures

What is the best way to match the nodes of two graphs? This graph alignm...

0 Judith Hermanns, et al. ∙

∙ 03/11/2021

SOFOS: Demonstrating the Challenges of Materialized View Selection on Knowledge Graphs

Analytical queries over RDF data are becoming prominent as a result of t...

0 Georgia Troullinou, et al. ∙

∙ 02/07/2021

Bandits for Learning to Explain from Explanations

We introduce Explearn, an online algorithm that learns to jointly output...

0 Freya Behrens, et al. ∙

∙ 09/29/2020

What if Neural Networks had SVDs?

Various Neural Networks employ time-consuming matrix operations like mat...

21 Alexander Mathiasen, et al. ∙

∙ 06/08/2020

FREDE: Linear-Space Anytime Graph Embeddings

Low-dimensional representations, or embeddings, of a graph's nodes facil...

6 Anton Tsitsulin, et al. ∙

∙ 05/27/2019

Intrinsic Multi-scale Evaluation of Generative Models

Generative models are often used to sample high-dimensional data points ...

5 Anton Tsitsulin, et al. ∙

∙ 11/15/2018

SGR: Self-Supervised Spectral Graph Representation Learning

Representing a graph as a vector is a challenging task; ideally, the rep...

0 Anton Tsitsulin, et al. ∙

∙ 03/13/2018

VERSE: Versatile Graph Embeddings from Similarity Measures

Embedding a web-scale information network into a low-dimensional vector ...

0 Anton Tsitsulin, et al. ∙

∙ 02/12/2018

Notable Characteristics Search through Knowledge Graphs

Query answering routinely employs knowledge graphs to assist the user in...

0 Davide Mottin, et al. ∙

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