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Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach.

, , , , , , , , , , , , , , , and . BMC Systems Biology, (2014)

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Compacting Neural Network Classifiers via Dropout Training., , and . CoRR, (2016)Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives., , , and . CoRR, (2018)Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion., , , , and . NeurIPS, page 8234-8244. (2018)Guided evolutionary strategies: augmenting random search with surrogate gradients., , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 4264-4273. PMLR, (2019)REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models., , , and . ICLR (Workshop), OpenReview.net, (2017)Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives., , , and . ICLR (Poster), OpenReview.net, (2019)Energy-Inspired Models: Learning with Sampler-Induced Distributions., , , and . CoRR, (2019)Model-Based Reinforcement Learning for Atari., , , , , , , , , and 3 other author(s). CoRR, (2019)Guided evolutionary strategies: escaping the curse of dimensionality in random search., , , and . CoRR, (2018)Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting., , , , , , , , and . CoRR, (2017)