brownian motion

Continuous Prediction with Experts' Advice JMLR 2024 Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling NeurIPS 2024 An Embedding-Dynamic Approach to Self-Supervised Learning WACV 2023 Inference on the Change Point under a High Dimensional Covariance Shift JMLR 2023 Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics JMLR 2023 Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior NeurIPS 2023 Sampling From a Schrödinger Bridge AISTATS 2023 Stabilizing GANs’ Training with Brownian Motion Controller ICML 2023 Differentiable Bayesian inference of SDE parameters using a pathwise series expansion of Brownian motion AISTATS 2022 Efficient and Accurate Gradients for Neural SDEs NeurIPS 2021 Heating up decision boundaries: isocapacitory saturation, adversarial scenarios and generalization bounds ICLR 2021 Neural SDEs as Infinite-Dimensional GANs ICML 2021 Noisy Adaptation Generates Lévy Flights in Attractor Neural Networks NeurIPS 2021 Variational Autoencoders with Riemannian Brownian Motion Priors ICML 2020 Optimistic optimization of a Brownian NeurIPS 2018 From random walks to distances on unweighted graphs NeurIPS 2015 Sparse Recovery with Brownian Sensing NeurIPS 2011