23 citations · 56 across the 7 of their papers we have counts for
7 papers
Virtual Screening on FPGA: Performance and Energy versus Effort
Tom Vander Aa, Tom Haber, Thomas J. Ashby +2
With their widespread availability, FPGA-based accelerators cards have become an alternative to GPUs and CPUs to accelerate computing in applications with certain requirements (lik…
Distributed Matrix Factorization using Asynchrounous Communication
Tom Vander Aa, Imen Chakroun, Tom Haber
Using the matrix factorization technique in machine learning is very common mainly in areas like recommender systems. Despite its high prediction accuracy and its ability to avoid…
Distributed Bayesian Probabilistic Matrix Factorization
Tom Vander Aa, Imen Chakroun, Tom Haber
Matrix factorization is a common machine learning technique for recommender systems. Despite its high prediction accuracy, the Bayesian Probabilistic Matrix Factorization algorithm…
Fast derivatives of likelihood functionals for ODE based models using adjoint-state method
Valdemar Melicher, Tom Haber, Wim Vanroose
We consider time series data modeled by ordinary differential equations (ODEs), widespread models in physics, chemistry, biology and science in general. The sensitivity analysis of…
Highly Scalable Tensor Factorization for Prediction of Drug-Protein Interaction Type
Adam Arany, Jaak Simm, Pooya Zakeri +5
The understanding of the type of inhibitory interaction plays an important role in drug design. Therefore, researchers are interested to know whether a drug has competitive or non-…
Macau: Scalable Bayesian Multi-relational Factorization with Side Information using MCMC
Jaak Simm, Adam Arany, Pooya Zakeri +5
We propose Macau, a powerful and flexible Bayesian factorization method for heterogeneous data. Our model can factorize any set of entities and relations that can be represented by…