# About

I am a PhD student at the Institute for Logic, Language, and Computation at the University of Amsterdam. My interests lie at the intersection of natural language processing and probabilistic modelling. In particular I work on inducing latent structure in parallel data and improving neural machine translation through better probabilistic modelling. My research is part of the European GoURMET project. My thesis adviser is dr. Wilker Ferreira Aziz.

### Current Interests

- Probabilistic Neural Machine Translation
- Deep Generative Models
- Bayesian Data Analysis
- Information Theory

### Resume

You can find my (slightly outdated) CV here.

### Selected Publications

**Sampling from Discrete Energy-Based Models with Quality/Efficiency Trade-offs**

Bryan Eikema, Germán Kruszewski, Hady Elsahar, Marc Dymetman in

*arXiv*, 2021

**Sampling-Based Minimum Bayes Risk Decoding for Neural Machine Translation**

Bryan Eikema and Wilker Aziz in

*arXiv*, 2021

**Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation**

Bryan Eikema and Wilker Aziz in

*Proceedings of the 28th International Conference on Computational Linguistics (COLING)*, 2020

*Best Paper Award*

### Talks

- Unbabel, ILLC CLS: The Inadequacy of the Mode in Neural Machine Translation
- COLING 2020: Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation