arXiv Statistics @arxiv_stats@qoto.org

Functional Tensors for Probabilistic Programming. (arXiv:1910.10775v1 [stat.ML]) http://arxiv.org/abs/1910.10775

Diversifying Database Activity Monitoring with Bandits. (arXiv:1910.10777v1 [cs.LG]) http://arxiv.org/abs/1910.10777

Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models. (arXiv:1910.10779v1 [econ.EM]) http://arxiv.org/abs/1910.10779

Hierarchical Transformers for Long Document Classification. (arXiv:1910.10781v1 [cs.CL]) http://arxiv.org/abs/1910.10781

Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks. (arXiv:1910.10783v1 [cs.LG]) http://arxiv.org/abs/1910.10783

High-Confidence Policy Optimization: Reshaping Ambiguity Sets in Robust MDPs. (arXiv:1910.10786v1 [cs.LG]) http://arxiv.org/abs/1910.10786

Predicting extremes: influenza epidemics in France. (arXiv:1910.10788v1 [stat.AP]) http://arxiv.org/abs/1910.10788

TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs. (arXiv:1909.02562v1 [cs.LG]) http://arxiv.org/abs/1909.02562

DeepEvolution: A Search-Based Testing Approach for Deep Neural Networks. (arXiv:1909.02563v1 [cs.LG]) http://arxiv.org/abs/1909.02563

Classification with Costly Features as a Sequential Decision-Making Problem. (arXiv:1909.02564v1 [cs.LG]) http://arxiv.org/abs/1909.02564

Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents. (arXiv:1909.02583v1 [cs.LG]) http://arxiv.org/abs/1909.02583

Additive function approximation in the brain. (arXiv:1909.02603v1 [cs.NE]) http://arxiv.org/abs/1909.02603

A Bayesian Approach to Multiple-Output Quantile Regression. (arXiv:1909.02623v1 [stat.ME]) http://arxiv.org/abs/1909.02623

Diversely Stale Parameters for Efficient Training of CNNs. (arXiv:1909.02625v1 [cs.LG]) http://arxiv.org/abs/1909.02625

Changepoint analysis of historical battle deaths. (arXiv:1909.02626v1 [stat.AP]) http://arxiv.org/abs/1909.02626

Contextual Minimum-Norm Estimates (CMNE): A Deep Learning Method for Source Estimation in Neuronal Networks. (arXiv:1909.02636v1 [q-bio.QM]) http://arxiv.org/abs/1909.02636

Intensity augmentation for domain transfer of whole breast segmentation in MRI. (arXiv:1909.02642v1 [eess.IV]) http://arxiv.org/abs/1909.02642

On perfectness in Gaussian graphical models. (arXiv:1909.01978v1 [math.ST]) http://arxiv.org/abs/1909.01978

Quasi-Newton Optimization Methods For Deep Learning Applications. (arXiv:1909.01994v1 [cs.LG]) http://arxiv.org/abs/1909.01994

Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning. (arXiv:1909.02005v1 [astro-ph.CO]) http://arxiv.org/abs/1909.02005