Papers
Robust Multi-fidelity Bayesian Optimization with Deep Kernel and Partition
Fengxue Zhang, Thomas Desautels, Yuxin Chen
Robust Offline Policy Learning with Observational Data from Multiple Sources
Aldo Gael Carranza, Susan Athey
Robust Score Matching
Richard Schwank, Andrew McCormack, Mathias Drton
ROTI-GCV: Generalized Cross-Validation for right-ROTationally Invariant Data
Kevin Luo, Yufan Li, Pragya Sur
RTD-Lite: Scalable Topological Analysis for Comparing Weighted Graphs in Learning Tasks
Eduard Tulchinskii, Daria Voronkova, Ilya Trofimov et al.
Safe exploration in reproducing kernel Hilbert spaces
Abdullah Tokmak, Kiran G. Krishnan, Thomas B. Schön et al.
Safety in the Face of Adversity: Achieving Zero Constraint Violation in Online Learning with Slowly Changing Constraints
Bassel Hamoud, Ilnura Usmanova, Kfir Yehuda Levy
Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses
Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain
Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics
Daniel Paulin, Peter A. Whalley, Neil K. Chada et al.
Sampling From Multiscale Densities With Delayed Rejection Generalized Hamiltonian Monte Carlo
Gilad Turok, Chirag Modi, Bob Carpenter
Sampling from the Random Linear Model via Stochastic Localization Up to the AMP Threshold
Han Cui, Zhiyuan Yu, Jingbo Liu
Sampling in High-Dimensions using Stochastic Interpolants and Forward-Backward Stochastic Differential Equations
Anand Jerry George, Nicolas Macris
Scalable Implicit Graphon Learning
Ali Azizpour, Nicolas Zilberstein, Santiago Segarra
Scalable Inference for Bayesian Multinomial Logistic-Normal Dynamic Linear Models
Manan Saxena, Tinghua Chen, Justin D Silverman
Scalable Out-of-Distribution Robustness in the Presence of Unobserved Confounders
Parjanya Prajakta Prashant, Seyedeh Baharan Khatami, Bruno Ribeiro et al.
Scalable spectral representations for multiagent reinforcement learning in network MDPs
Zhaolin Ren, Runyu Zhang, Bo Dai et al.
S-CFE: Simple Counterfactual Explanations
Shpresim Sadiku, Moritz Wagner, Sai Ganesh Nagarajan et al.
ScoreFusion: Fusing Score-based Generative Models via Kullback–Leibler Barycenters
Hao Liu, Tony Junze Ye, Jose Blanchet et al.
Score matching for bridges without learning time-reversals
Elizabeth Louise Baker, Moritz Schauer, Stefan Sommer
Selecting the Number of Communities for Weighted Degree-Corrected Stochastic Block Models
Yucheng Liu, Xiaodong Li
Semiparametric conformal prediction
Ji Won Park, Kyunghyun Cho
SemlaFlow – Efficient 3D Molecular Generation with Latent Attention and Equivariant Flow Matching
Ross Irwin, Alessandro Tibo, Jon Paul Janet et al.
Separation-Based Distance Measures for Causal Graphs
Jonas Wahl, Jakob Runge
Sequential Kernelized Stein Discrepancy
Diego Martinez-Taboada, Aaditya Ramdas
Signal Recovery from Random Dot-Product Graphs under Local Differential Privacy
Siddharth Vishwanath, Jonathan Hehir