Papers
938 papers found
Ordinal causal discovery
Yang Ni, Bani Mallick
Orthogonal Gromov-Wasserstein discrepancy with efficient lower bound
Hongwei Jin, Zishun Yu, Xinhua Zhang
PAC-Bayesian domain adaptation bounds for multiclass learners
Anthony Sicilia, Katherine Atwell, Malihe Alikhani et al.
Partial likelihood Thompson sampling
Han Wu, Stefan Wager
Partially adaptive regularized multiple regression analysis for estimating linear causal effects
Hisayoshi Nanmo, Manabu Kuroki
PathFlow: A normalizing flow generator that finds transition paths
Tianyi Liu, Weihao Gao, Zhirui Wang et al.
PDQ-Net: Deep probabilistic dual quaternion network for absolute pose regression on $SE(3)$
Wenjie Li, Wasif Naeem, Jia Liu et al.
Perturbation type categorization for multiple adversarial perturbation robustness
Pratyush Maini, Xinyun Chen, Bo Li et al.
Physics guided neural networks for spatio-temporal super-resolution of turbulent flows
Tianshu Bao, Shengyu Chen, Taylor T Johnson et al.
Predictive Whittle networks for time series
Zhongjie Yu, Fabrizio Ventola, Nils Thoma et al.
Principle of relevant information for graph sparsification
Shujian Yu, Francesco Alesiani, Wenzhe Yin et al.
Privacy-aware compression for federated data analysis
Kamalika Chaudhuri, Chuan Guo, Mike Rabbat
Probabilistic spatial transformer networks
Pola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen et al.
Probabilistic surrogate networks for simulators with unbounded randomness
Andreas Munk, Berend Zwartsenberg, Adam Ścibior et al.
Proportional allocation of indivisible resources under ordinal and uncertain preferences.
Zihao Li, Xiaohui Bei, Zhenzhen Yan
Quadratic metric elicitation for fairness and beyond
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan et al.
Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison
Eyke Hüllermeier, Sébastien Destercke, Mohammad Hossein Shaker
Quantum perceptron revisited: Computational-statistical tradeoffs
Mathieu Roget, Giuseppe Di Molfetta, Hachem Kadri
Recursive Monte Carlo and variational inference with auxiliary variables
Alexander K. Lew, Marco Cusumano-Towner, Vikash K. Mansinghka
Reframed GES with a neural conditional dependence measure
Xinwei Shen, Shengyu Zhu, Jiji Zhang et al.
Regret guarantees for model-based reinforcement learning with long-term average constraints
Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal
Reinforcement learning in many-agent settings under partial observability
Keyang He, Prashant Doshi, Bikramjit Banerjee
Research on video adversarial attack with long living cycle
Zeyu Zhao, Ke Xu, Xinghao Jiang et al.
Residual bootstrap exploration for stochastic linear bandit
Shuang Wu, Chi-Hua Wang, Yuantong Li et al.