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Joeri Hermans - Publications ORBI
Louppe, G., Hermans, J., & Cranmer, K. (2019). Adversarial Variational Optimization of Non-Differentiable Simulators. Proceedings of Machine Learning Research.
Peer reviewed
Complex computer simulators are increasingly used across fields of science as generative models tying parameters of an underlying theory to experimental observations. Inference in this setup is often difficult ...
Hermans, J., Begy, V., & Louppe, G. (2019). Likelihood-free MCMC with Approximate Likelihood Ratios. Eprint/Working paper retrieved from https://arxiv.org/abs/1903.04057.
We propose a novel approach for posterior sampling with intractable likelihoods. This is an increasingly important problem in scientific applications where models are implemented as sophisticated computer ...
Hermans, J., & Louppe, G. (2018). Gradient Energy Matching for Distributed Asynchronous Gradient Descent. Eprint/Working paper retrieved from https://arxiv.org/abs/1805.08469.
Distributed asynchronous SGD has become widely used for deep learning in large-scale systems, but remains notorious for its instability when increasing the number of workers. In this work, we study the ...