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4 papers · 1 filter
Inference and Learning for Generative Capsule Models
Alfredo Nazabal, Nikolaos Tsagkas, Christopher K. I. Williams
Capsule networks (see e.g. Hinton et al., 2018) aim to encode knowledge of and reason about the relationship between an object and its parts. In this paper we specify a generative…
State-of-the-art generalisation research in NLP: A taxonomy and review
Dieuwke Hupkes, Mario Giulianelli, Verna Dankers +17
The ability to generalise well is one of the primary desiderata of natural language processing (NLP). Yet, what 'good generalisation' entails and how it should be evaluated is not…
Formant Tracking Using Quasi-Closed Phase Forward-Backward Linear Prediction Analysis and Deep Neural Networks
Dhananjaya Gowda, Bajibabu Bollepalli, Sudarsana Reddy Kadiri +1
Formant tracking is investigated in this study by using trackers based on dynamic programming (DP) and deep neural nets (DNNs). Using the DP approach, six formant estimation method…
GROMACS in the cloud: A global supercomputer to speed up alchemical drug design
Carsten Kutzner, Christian Kniep, Austin Cherian +4
We assess costs and efficiency of state-of-the-art high performance cloud computing compared to a traditional on-premises compute cluster. Our use case are atomistic simulations ca…