Dennis Ulmer | DeepAI

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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...

0 Joris Baan, et al. ∙

∙ 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 ...

4 Dennis Ulmer, et al. ∙

∙ 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...

50 Dennis Ulmer, et al. ∙

∙ 10/06/2021

A Survey on Evidential Deep Learning For Single-Pass Uncertainty Estimation

Popular approaches for quantifying predictive uncertainty in deep neural...

2 Dennis Ulmer, et al. ∙

∙ 01/03/2021

Recoding latent sentence representations – Dynamic gradient-based activation modification in RNNs

In Recurrent Neural Networks (RNNs), encoding information in a suboptima...

6 Dennis Ulmer, et al. ∙

∙ 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...

13 Dennis Ulmer, et al. ∙

∙ 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...

7 Dennis Ulmer, et al. ∙

∙ 06/07/2019

Assessing incrementality in sequence-to-sequence models

Since their inception, encoder-decoder models have successfully been app...

0 Dennis Ulmer, et al. ∙

∙ 06/04/2019

On the Realization of Compositionality in Neural Networks

We present a detailed comparison of two types of sequence to sequence mo...

0 Joris Baan, et al. ∙

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