Papers
4,122 papers found
Axiomatic effect propagation in structural causal models
Raghav Singal, George Michailidis
Bagging Provides Assumption-free Stability
Jake A. Soloff, Rina Foygel Barber, Rebecca Willett
Bayesian Regression Markets
Thomas Falconer, Jalal Kazempour, Pierre Pinson
Bayesian Structural Learning with Parametric Marginals for Count Data: An Application to Microbiota Systems
Veronica Vinciotti, Pariya Behrouzi, Reza Mohammadi
BenchMARL: Benchmarking Multi-Agent Reinforcement Learning
Matteo Bettini, Amanda Prorok, Vincent Moens
Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box
Ryan Giordano, Martin Ingram, Tamara Broderick
Boundary constrained Gaussian processes for robust physics-informed machine learning of linear partial differential equations
David Dalton, Alan Lazarus, Hao Gao et al.
Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds
Hao Liang, Zhi-Quan Luo
Causal Discovery with Generalized Linear Models through Peeling Algorithms
Minjie Wang, Xiaotong Shen, Wei Pan
Causal effects of intervening variables in settings with unmeasured confounding
Lan Wen, Aaron Sarvet, Mats Stensrud
Causal-learn: Causal Discovery in Python
Yujia Zheng, Biwei Huang, Wei Chen et al.
Characterization of translation invariant MMD on Rd and connections with Wasserstein distances
Thibault Modeste, Clément Dombry
Choosing the Number of Topics in LDA Models – A Monte Carlo Comparison of Selection Criteria
Victor Bystrov, Viktoriia Naboka-Krell, Anna Staszewska-Bystrova et al.
Classification of Data Generated by Gaussian Mixture Models Using Deep ReLU Networks
Tian-Yi Zhou, Xiaoming Huo
Classification with Deep Neural Networks and Logistic Loss
Zihan Zhang, Lei Shi, Ding-Xuan Zhou
Cluster-Adaptive Network A/B Testing: From Randomization to Estimation
Yang Liu, Yifan Zhou, Ping Li et al.
Compressed and distributed least-squares regression: convergence rates with applications to federated learning
Constantin Philippenko, Aymeric Dieuleveut
Conformal Inference for Online Prediction with Arbitrary Distribution Shifts
Isaac Gibbs, Emmanuel J. Candès
Consistent Multiclass Algorithms for Complex Metrics and Constraints
Harikrishna Narasimhan, Harish G. Ramaswamy, Shiv Kumar Tavker et al.
Contamination-source based K-sample clustering
Xavier Milhaud, Denys Pommeret, Yahia Salhi et al.
Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression
Aleksandrs Slivkins, Xingyu Zhou, Karthik Abinav Sankararaman et al.
Continuous Prediction with Experts' Advice
Nicholas J. A. Harvey, Christopher Liaw, Victor S. Portella