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07/28/2023
Uncertainty in Natural Language Generation: From Theory to Applications
Recent advances of powerful Language Models have allowed Natural Languag...
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04/14/2022
deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks
A lot of Machine Learning (ML) and Deep Learning (DL) research is of an ...
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04/13/2022
Experimental Standards for Deep Learning Research: A Natural Language Processing Perspective
The field of Deep Learning (DL) has undergone explosive growth during th...
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10/06/2021
A Survey on Evidential Deep Learning For Single-Pass Uncertainty Estimation
Popular approaches for quantifying predictive uncertainty in deep neural...
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01/03/2021
Recoding latent sentence representations – Dynamic gradient-based activation modification in RNNs
In Recurrent Neural Networks (RNNs), encoding information in a suboptima...
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12/09/2020
Know Your Limits: Monotonicity Softmax Make Neural Classifiers Overconfident on OOD Data
A crucial requirement for reliable deployment of deep learning models fo...
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11/06/2020
Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data
When deploying machine learning models in high-stakes real-world environ...
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06/07/2019
Assessing incrementality in sequence-to-sequence models
Since their inception, encoder-decoder models have successfully been app...
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06/04/2019
