JMLR · Scour

A Common Interface for Automatic Differentiation

skwdro: a library for Wasserstein distributionally robust machine learning

Two-way Node Popularity Model for Directed and Bipartite Networks

Neural Network Parameter-optimization of Gaussian Pre-marginalized Directed Acyclic Graphs

Generative Bayesian Inference with GANs

Nonlinear function-on-function regression by RKHS

Communication-efficient Distributed Statistical Inference for Massive Data with Heterogeneous Auxiliary Information

Online Detection of Changes in Moment--Based Projections: When to Retrain Deep Learners or Update Portfolios?

CHANI: Correlation-based Hawkes Aggregation of Neurons with bio-Inspiration

Refined Risk Bounds for Unbounded Losses via Transductive Priors

A causal fused lasso for interpretable heterogeneous treatment effects estimation

Simulation-based Calibration of Uncertainty Intervals under Approximate Bayesian Estimation

Decorrelated Local Linear Estimator: Inference for Non-linear Effects in High-dimensional Additive Models

Error Analysis for Deep ReLU Feedforward Density-Ratio Estimation with Bregman Divergence

Unsupervised Feature Selection via Nonnegative Orthogonal Constrained Regularized Minimization

Adaptive Forward Stepwise: A Method for High Sparsity Regression

Nonparametric Estimation of a Factorizable Density using Diffusion Models

Learning Bayesian Network Classifiers to Minimize Class Variable Parameters

Hierarchical Causal Models

Reparameterized Complex-valued Neurons Can Efficiently Learn More than Real-valued Neurons via Gradient Descent

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