According to our database1, Leonard Hasenclever authored at least 5 papers between 2014 and 2018.
Legend:Book In proceedings Article PhD thesis Other
Sylvester Normalizing Flows for Variational Inference.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018
Mix & Match Agent Curricula for Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018
Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server.
Journal of Machine Learning Research, 2017
Relativistic Monte Carlo.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
An investigation into irreducible autocatalytic sets and power law distributed catalysis.
Natural Computing, 2014