Publications  

Multiplicative LSTM

Multiplicative long short-term memory (mLSTM) is recurrent neural network architecture designed primarily for sequence modelling. mLSTM combines a multiplicative RNN and an LSTM. mLSTM was used by Open AI for sentiment analysis, and by Tilde for neural machine translation.

Krause, B., Lu, L., Murray, I., & Renals, S. (2016). Multiplicative LSTM for sequence modelling. arXiv:1609.07959.

Dynamic Evaluation

Dynamic evaluation is a method for gradient based adaptation to sequence history that can exploit re-occurring sequential patterns. I explored and developed dynamic evaluation methodology to improve the state-of-the-art at several commonly benchmarked character and word-level language modelling tasks. This work was published at ICML 2018.

Krause, B., Kahembwe, E., Murray, I., & Renals, S. (2018). Dynamic Evaluation of Neural Sequence Models. ICML 2018.

Conversational AI

During my time working on the Amazon Alexa prize, I developed data driven methods for building open domain conversation agents that combined retrieval and generative approaches, and contributed to the development of a new data collection technique called self-dialogues. Our conversation corpus collected from Amazon Mechanical Turk is publicly available here.

Krause, B., Damonte, M., Dobre, M., ... & Webber, B. (2017). Edina: Building an Open Domain Socialbot with Self-dialogues. arXiv:1709.09816.

Optimization

My master's thesis and my early PhD work explored Hessian-free optimization in LSTMs

Krause, B. (2015). Optimizing and Contrasting Recurrent Neural Network Architectures. arXiv:1510.04953.

Krause, B., Lu, L., Murray, I., & Renals, S. (2015). On the Efficiency of Recurrent Neural Network Optimization Algorithms. NIPS Workshop on Optimization for Machine Learning, Montreal, Canada, 2015.

Neuroimaging

I also have past neuroimaging research studying the role of neurotransmitters in brain blood flow and schizophrenia

Krause, B. W., Wijtenburg, S. A., Holcomb, H. H., Kochunov, P., Wang, D. J., Hong, L. E., & Rowland, L. M. (2014). Anterior cingulate GABA levels predict whole-brain cerebral blood flow. Neuroscience letters, 561, 188-191.

Rowland, L. M., Krause, B. W., Wijtenburg, S. A., McMahon, R. P., Chiappelli, J., Nugent, K. L., ... & Hong, L. E. (2016). Medial frontal GABA is lower in older schizophrenia: a MEGA-PRESS with macromolecule suppression study. Molecular psychiatry, 21(2), 198-204.

Korenic, S. A., Nisonger, S. J., Krause, B. W., Wijtenburg, S. A., Hong, L. E., & Rowland, L. M. (2016). Effectiveness of fast mapping to promote learning in schizophrenia. Schizophrenia Research: Cognition, 4, 24-31.