Papers
4,122 papers found
The Brier Score under Administrative Censoring: Problems and a Solution
Håvard Kvamme, Ørnulf Borgan
The d-Separation Criterion in Categorical Probability
Tobias Fritz, Andreas Klingler
The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima
Peter L. Bartlett, Philip M. Long, Olivier Bousquet
The Geometry and Calculus of Losses
Robert C. Williamson, Zac Cranko
The Hyperspherical Geometry of Community Detection: Modularity as a Distance
Martijn Gösgens, Remco van der Hofstad, Nelly Litvak
The Implicit Bias of Benign Overfitting
Ohad Shamir
The Measure and Mismeasure of Fairness
Sam Corbett-Davies, Johann D. Gaebler, Hamed Nilforoshan et al.
The multimarginal optimal transport formulation of adversarial multiclass classification
Nicolás García Trillos, Matt Jacobs, Jakwang Kim
The Power of Contrast for Feature Learning: A Theoretical Analysis
Wenlong Ji, Zhun Deng, Ryumei Nakada et al.
The Proximal ID Algorithm
Ilya Shpitser, Zach Wood-Doughty, Eric J. Tchetgen Tchetgen
The SKIM-FA Kernel: High-Dimensional Variable Selection and Nonlinear Interaction Discovery in Linear Time
Raj Agrawal, Tamara Broderick
Topological Convolutional Layers for Deep Learning
Ephy R. Love, Benjamin Filippenko, Vasileios Maroulas et al.
Topological Hidden Markov Models
Adam B Kashlak, Prachi Loliencar, Giseon Heo
Torchhd: An Open Source Python Library to Support Research on Hyperdimensional Computing and Vector Symbolic Architectures
Mike Heddes, Igor Nunes, Pere Vergés et al.
TorchOpt: An Efficient Library for Differentiable Optimization
Jie Ren*, Xidong Feng*, Bo Liu* et al.
Towards Learning to Imitate from a Single Video Demonstration
Glen Berseth, Florian Golemo, Christopher Pal
Tree-AMP: Compositional Inference with Tree Approximate Message Passing
Antoine Baker, Florent Krzakala, Benjamin Aubin et al.
Two Sample Testing in High Dimension via Maximum Mean Discrepancy
Hanjia Gao, Xiaofeng Shao
Unbiased Multilevel Monte Carlo Methods for Intractable Distributions: MLMC Meets MCMC
Tianze Wang, Guanyang Wang
Universal Approximation Property of Invertible Neural Networks
Isao Ishikawa, Takeshi Teshima, Koichi Tojo et al.
Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data
Vaidotas Simkus, Benjamin Rhodes, Michael U. Gutmann
Variational Inference for Deblending Crowded Starfields
Runjing Liu, Jon D. McAuliffe, Jeffrey Regier et al.
Variational Inverting Network for Statistical Inverse Problems of Partial Differential Equations
Junxiong Jia, Yanni Wu, Peijun Li et al.
VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback
Kirthevasan Kandasamy, Joseph E Gonzalez, Michael I Jordan et al.