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Integral Probability Metrics Meet Neural Networks: The Radon-Kolmogorov-Smirnov Test
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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On Inference for the Support Vector Machine
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Random Pruning Over-parameterized Neural Networks Can Improve Generalization: A Training Dynamics Analysis
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Implicit vs Unfolded Graph Neural Networks
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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GraphNeuralNetworks.jl: Deep Learning on Graphs with Julia
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Dynamic angular synchronization under smoothness constraints
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Derivative-Informed Neural Operator Acceleration of Geometric MCMC for Infinite-Dimensional Bayesian Inverse Problems
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Wasserstein F-tests for Frechet regression on Bures-Wasserstein manifolds
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Distributed Stochastic Bilevel Optimization: Improved Complexity and Heterogeneity Analysis
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Learning causal graphs via nonlinear sufficient dimension reduction
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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On Consistent Bayesian Inference from Synthetic Data
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Optimization Over a Probability Simplex
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Laplace Meets Moreau: Smooth Approximation to Infimal Convolutions Using Laplace's Method
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Sampling and Estimation on Manifolds using the Langevin Diffusion
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Sharp Bounds for Sequential Federated Learning on Heterogeneous Data
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Local Linear Recovery Guarantee of Deep Neural Networks at Overparameterization
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Stabilizing Sharpness-Aware Minimization Through A Simple Renormalization Strategy
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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Fine-Grained Change Point Detection for Topic Modeling with Pitman-Yor Process
Published in JMLR (2026)Subjects: “…Artificial Intelligence & Machine Learning…”
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