arXiv Statistics @arxiv_stats@qoto.org

Bayesian mitigation of spatial coarsening for a fairly flexible spatiotemporal Hawkes model. (arXiv:2010.02994v1 [stat.ME]) http://arxiv.org/abs/2010.02994

Flow-based anomaly detection. (arXiv:2010.03002v1 [cs.LG]) http://arxiv.org/abs/2010.03002

Using Bayesian deep learning approaches for uncertainty-aware building energy surrogate models. (arXiv:2010.03029v1 [stat.ML]) http://arxiv.org/abs/2010.03029

Using Experimental Data to Evaluate Methods for Observational Causal Inference. (arXiv:2010.03051v1 [stat.ME]) http://arxiv.org/abs/2010.03051

Sequential Changepoint Detection in Neural Networks with Checkpoints. (arXiv:2010.03053v1 [cs.LG]) http://arxiv.org/abs/2010.03053

Is the Best Better? Bayesian Statistical Model Comparison for Natural Language Processing. (arXiv:2010.03088v1 [cs.CL]) http://arxiv.org/abs/2010.03088

Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective. (arXiv:2010.03104v1 [cs.LG]) http://arxiv.org/abs/2010.03104

Dealing with multiple testing: To adjust or not to adjust. (arXiv:2010.02205v1 [stat.OT]) http://arxiv.org/abs/2010.02205

Likelihood-based solution to the Monty Hall puzzle and a related 3-prisoner paradox. (arXiv:2010.02211v1 [stat.OT]) http://arxiv.org/abs/2010.02211

A new Framework for Causal Discovery. (arXiv:2010.02247v1 [stat.ME]) http://arxiv.org/abs/2010.02247

Forecasting COVID-19 daily cases using phone call data. (arXiv:2010.02252v1 [stat.AP]) http://arxiv.org/abs/2010.02252

Temporal Difference Uncertainties as a Signal for Exploration. (arXiv:2010.02255v1 [cs.AI]) http://arxiv.org/abs/2010.02255

Subspace Embeddings Under Nonlinear Transformations. (arXiv:2010.02264v1 [cs.LG]) http://arxiv.org/abs/2010.02264

Detecting approximate replicate components of a high-dimensional random vector with latent structure. (arXiv:2010.02288v1 [stat.ME]) http://arxiv.org/abs/2010.02288

Latent World Models For Intrinsically Motivated Exploration. (arXiv:2010.02302v1 [cs.LG]) http://arxiv.org/abs/2010.02302

A Power Analysis of the Conditional Randomization Test and Knockoffs. (arXiv:2010.02304v1 [math.ST]) http://arxiv.org/abs/2010.02304

Deep Anomaly Detection by Residual Adaptation. (arXiv:2010.02310v1 [cs.LG]) http://arxiv.org/abs/2010.02310

Evaluating Progress on Machine Learning for Longitudinal Electronic Healthcare Data. (arXiv:2010.01149v1 [cs.LG]) http://arxiv.org/abs/2010.01149

Representational aspects of depth and conditioning in normalizing flows. (arXiv:2010.01155v1 [cs.LG]) http://arxiv.org/abs/2010.01155

Data-Driven Assessment of Deep Neural Networks with Random Input Uncertainty. (arXiv:2010.01171v1 [cs.LG]) http://arxiv.org/abs/2010.01171