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08/16/2023
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations
Prototypical parts-based networks are becoming increasingly popular due ...
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06/18/2023
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging
Multiple Instance Learning (MIL) is a weakly-supervised problem in which...
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03/14/2023
ICICLE: Interpretable Class Incremental Continual Learning
Continual learning enables incremental learning of new tasks without for...
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01/28/2023
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts
We introduce ProtoSeg, a novel model for interpretable semantic image se...
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10/07/2022
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction
In this work, we propose the novel Prototypical Graph Regression Self-ex...
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12/06/2021
Interpretable Image Classification with Differentiable Prototypes Assignment
We introduce ProtoPool, an interpretable image classification model with...
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08/24/2021
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Fine-Grained Interpretability
Multiple Instance Learning (MIL) gains popularity in many real-life mach...
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12/02/2020
Classifying bacteria clones using attention-based deep multiple instance learning interpreted by persistence homology
In this work, we analyze if it is possible to distinguish between differ...
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11/29/2020
ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery
In this paper, we introduce ProtoPShare, a self-explained method that in...
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05/25/2020
Kernel Self-Attention in Deep Multiple Instance Learning
Multiple Instance Learning (MIL) is weakly supervised learning, which as...
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05/24/2020
Deep learning approach to describe and classify fungi microscopic images
Preliminary diagnosis of fungal infections can rely on microscopic exami...
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06/22/2019