Lucie Charlotte Magister | DeepAI

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∙ 07/01/2023

SHARCS: Shared Concept Space for Explainable Multimodal Learning

Multimodal learning is an essential paradigm for addressing complex real...

0 Gabriele Dominici, et al. ∙

∙ 05/17/2023

Deep Multiple Instance Learning with Distance-Aware Self-Attention

Traditional supervised learning tasks require a label for every instance...

0 Georg Wölflein, et al. ∙

∙ 04/27/2023

Interpretable Neural-Symbolic Concept Reasoning

Deep learning methods are highly accurate, yet their opaque decision pro...

0 Pietro Barbiero, et al. ∙

∙ 02/09/2023

GCI: A (G)raph (C)oncept (I)nterpretation Framework

Explainable AI (XAI) underwent a recent surge in research on concept ext...

7 Dmitry Kazhdan, et al. ∙

∙ 12/16/2022

Teaching Small Language Models to Reason

Chain of thought prompting successfully improves the reasoning capabilit...

0 Lucie Charlotte Magister, et al. ∙

∙ 08/22/2022

Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis

Graph neural networks (GNNs) are highly effective on a variety of graph-...

0 Han Xuanyuan, et al. ∙

∙ 07/27/2022

Encoding Concepts in Graph Neural Networks

The opaque reasoning of Graph Neural Networks induces a lack of human tr...

0 Lucie Charlotte Magister, et al. ∙

∙ 07/25/2021

GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks

While graph neural networks (GNNs) have been shown to perform well on gr...

0 Lucie Charlotte Magister, et al. ∙

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