Papers
4,122 papers found
Enhancing Graph Representation Learning with Localized Topological Features
Zuoyu Yan, Qi Zhao, Ze Ye et al.
Equivariant Manifold Neural ODEs and Differential Invariants
Emma Andersdotter, Daniel Persson, Fredrik Ohlsson
Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalities
Rocco Caprio, Juan Kuntz, Samuel Power et al.
Error estimation and adaptive tuning for unregularized robust M-estimator
Pierre C. Bellec, Takuya Koriyama
Estimating Network-Mediated Causal Effects via Principal Components Network Regression
Alex Hayes, Mark M. Fredrickson, Keith Levin
Estimation of Local Geometric Structure on Manifolds from Noisy Data
Yariv Aizenbud, Barak Sober
Evaluation of Active Feature Acquisition Methods for Time-varying Feature Settings
Henrik von Kleist, Alireza Zamanian, Ilya Shpitser et al.
Exponential Family Graphical Models: Correlated Replicates and Unmeasured Confounders, with Applications to fMRI Data
Yanxin Jin, Yang Ning, Kean Ming Tan
Extending Temperature Scaling with Homogenizing Maps
Christopher Qian, Feng Liang, Jason Adams
Extremal graphical modeling with latent variables via convex optimization
Sebastian Engelke, Armeen Taeb
Fair Text Classification via Transferable Representations
Thibaud Leteno, Michael Perrot, Charlotte Laclau et al.
Fast Algorithm for Constrained Linear Inverse Problems
Mohammed Rayyan Sheriff, Floor Fenne Redel, Peyman Mohajerin Esfahani
Feature Learning in Finite-Width Bayesian Deep Linear Networks with Multiple Outputs and Convolutional Layers
Federico Bassetti, Marco Gherardi, Alessandro Ingrosso et al.
FedHB: Hierarchical Bayesian Federated Learning
Minyoung Kim, Timothy Hospedales
Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems
Michal Dereziński, Daniel LeJeune, Deanna Needell et al.
Fine-Grained Change Point Detection for Topic Modeling with Pitman-Yor Process
Feifei Wang, Zimeng Zhao, Ruimin Ye et al.
Finite Expression Method for Solving High-Dimensional Partial Differential Equations
Senwei Liang, Haizhao Yang
Four Axiomatic Characterizations of the Integrated Gradients Attribution Method
Daniel Lundstrom, Meisam Razaviyayn
Frequentist Guarantees of Distributed (Non)-Bayesian Inference
Bohan Wu, César A. Uribe
From Sparse to Dense Functional Data in High Dimensions: Revisiting Phase Transitions from a Non-Asymptotic Perspective
Shaojun Guo, Dong Li, Xinghao Qiao et al.
Frontiers to the learning of nonparametric hidden Markov models
Kweku Abraham, Elisabeth Gassiat, Zacharie Naulet
Fundamental Limits of Membership Inference Attacks on Machine Learning Models
Eric Aubinais, Elisabeth Gassiat, Pablo Piantanida
FusionBench: A Unified Library and Comprehensive Benchmark for Deep Model Fusion
Anke Tang, Li Shen, Yong Luo et al.
Generalized multi-view model: Adaptive density estimation under low-rank constraints
Julien Chhor, Olga Klopp, Alexandre B. Tsybakov