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05/04/2023
Interpretable Sentence Representation with Variational Autoencoders and Attention
In this thesis, we develop methods to enhance the interpretability of re...
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06/22/2022
Towards Unsupervised Content Disentanglement in Sentence Representations via Syntactic Roles
Linking neural representations to linguistic factors is crucial in order...
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05/12/2022
Exploiting Inductive Bias in Transformers for Unsupervised Disentanglement of Syntax and Semantics with VAEs
We propose a generative model for text generation, which exhibits disent...
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09/27/2021
Challenging the Semi-Supervised VAE Framework for Text Classification
Semi-Supervised Variational Autoencoders (SSVAEs) are widely used models...
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12/24/2020
Disentangling semantics in language through VAEs and a certain architectural choice
We present an unsupervised method to obtain disentangled representations...
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10/13/2020
Controlling the Interaction Between Generation and Inference in Semi-Supervised Variational Autoencoders Using Importance Weighting
Even though Variational Autoencoders (VAEs) are widely used for semi-sup...
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09/19/2019
Slices of Attention in Asynchronous Video Job Interviews
The impact of non verbal behaviour in a hiring decision remains an open ...
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07/25/2019
