Search Results for author:
Found 8 papers, 2 papers with code
On The Potential of The Fractal Geometry and The CNNs Ability to Encode it
In this work, we investigate the features that are learned by deep models and we study whether these deep networks are able to encode features as complex and high-level as the fractal dimensions.
CEnt: An Entropy-based Model-agnostic Explainability Framework to Contrast Classifiers' Decisions
Our Contrastive Entropy-based explanation method, CEnt, approximates a model locally by a decision tree to compute entropy information of different feature splits.
Beyond Model Interpretability: On the Faithfulness and Adversarial Robustness of Contrastive Textual Explanations
Accordingly, we extend the computation of three metrics, proximity, connectedness and stability, to textual data and we benchmark two successful contrastive methods, POLYJUICE and MiCE, on our suggested metrics.
On the Explainability of Natural Language Processing Deep Models
Such challenges can be attributed to the lack of input structure in textual data, the use of word embeddings that add to the opacity of the models and the difficulty of the visualization of the inner workings of deep models when they are trained on textual data.
On the Evaluation of the Plausibility and Faithfulness of Sentiment Analysis Explanations
In this work, inspired by offline information retrieval, we propose different metrics and techniques to evaluate the explainability of SA models from two angles.
An Optimized and Energy-Efficient Parallel Implementation of Non-Iteratively Trained Recurrent Neural Networks
Recurrent neural networks (RNN) have been successfully applied to various sequential decision-making tasks, natural language processing applications, and time-series predictions.
Change your singer: a transfer learning generative adversarial framework for song to song conversion
Transfer learning improves the GV by 35% and the MS by 13% on average.
TopoText: Interactive Digital Mapping of Literary Text
TopoText calculates the number of times a place was mentioned in the text, which is then reflected on the map allowing the end-user to grasp the importance of the different places within the text.
