Papers
Cost-aware simulation-based inference
Ayush Bharti, Daolang Huang, Samuel Kaski et al.
Counting Graphlets of Size k under Local Differential Privacy
Vorapong Suppakitpaisarn, Donlapark Ponnoprat, Nicha Hirankarn et al.
Covariance Selection over Networks
Wenfu Xia, Fengpei Li, Ying Sun et al.
Credal Two-Sample Tests of Epistemic Uncertainty
Siu Lun Chau, Antonin Schrab, Arthur Gretton et al.
Credibility-Aware Multimodal Fusion Using Probabilistic Circuits
Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur et al.
Cross-Modal Imputation and Uncertainty Estimation for Spatial Transcriptomics
Xiangyu Guo, Ricardo Henao
Cross-modality Matching and Prediction of Perturbation Responses with Labeled Gromov-Wasserstein Optimal Transport
Jayoung Ryu, Charlotte Bunne, Luca Pinello et al.
Cross Validation for Correlated Data in Classification Models
Oren Yuval, Saharon Rosset
Cubic regularized subspace Newton for non-convex optimization
Jim Zhao, Nikita Doikov, Aurelien Lucchi
Data-Driven Upper Confidence Bounds with Near-Optimal Regret for Heavy-Tailed Bandits
Ambrus Tamás, Szabolcs Szentpéteri, Balázs Csáji
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
Sheng Liu, Zihan Wang, Yuxiao Chen et al.
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows
Jonathan Geuter, Clément Bonet, Anna Korba et al.
DeCaf: A Causal Decoupling Framework for OOD Generalization on Node Classification
Xiaoxue Han, Huzefa Rangwala, Yue Ning
Decision from Suboptimal Classifiers: Excess Risk Pre- and Post-Calibration
Alexandre Perez-Lebel, Gael Varoquaux, Sanmi Koyejo et al.
Decision-Point Guided Safe Policy Improvement
Abhishek Sharma, Leo Benac, Sonali Parbhoo et al.
Decoupling epistemic and aleatoric uncertainties with possibility theory
Nong Minh Hieu, Jeremie Houssineau, Neil K. Chada et al.
Deep Clustering via Probabilistic Ratio-Cut Optimization
Ayoub Ghriss, Claire Monteleoni
Deep Generative Quantile Bayes
Jungeum Kim, Percy S. Zhai, Veronika Rockova
Deep Optimal Sensor Placement for Black Box Stochastic Simulations
Paula Cordero Encinar, Tobias Schröder, Peter Yatsyshin et al.
Density-Dependent Group Testing
Rahil Morjaria, Saikiran Bulusu, Venkata Gandikota et al.
Density Ratio-based Proxy Causal Learning Without Density Ratios
Bariscan Bozkurt, Ben Deaner, Dimitri Meunier et al.
Density Ratio Estimation via Sampling along Generalized Geodesics on Statistical Manifolds
Masanari Kimura, Howard Bondell
Differentiable Calibration of Inexact Stochastic Simulation Models via Kernel Score Minimization
Ziwei Su, Diego Klabjan
Differentiable Causal Structure Learning with Identifiability by NOTIME
Jeroen Berrevoets, Jakob Raymaekers, Mihaela van der Schaar et al.
Differentially private algorithms for linear queries via stochastic convex optimization
Giorgio Micali, Clement LEZANE, Annika Betken