3 papers
stat.ML2021
Robust and integrative Bayesian neural networks for likelihood-free parameter inference
Fredrik Wrede, Robin Eriksson, Richard Jiang +4
State-of-the-art neural network-based methods for learning summary statistics have delivered promising results for simulation-based likelihood-free parameter inference. Existing ap…
stat.ML2020
Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation
Mattias Åkesson, Prashant Singh, Fredrik Wrede +1
Approximate Bayesian Computation is widely used in systems biology for inferring parameters in stochastic gene regulatory network models. Its performance hinges critically on the a…
cs.DC2019
Adapting The Secretary Hiring Problem for Optimal Hot-Cold Tier Placement under Top- Workloads
Ben Blamey, Fredrik Wrede, Johan Karlsson +2
Top-K queries are an established heuristic in information retrieval. This paper presents an approach for optimal tiered storage allocation under stream processing workloads using t…