Stochastic Processes

Flow Annealed Importance Sampling Bootstrap ICLR 2023 Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts NeurIPS 2023 Forget Unlearning: Towards True Data-Deletion in Machine Learning ICML 2023 Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space ICML 2023 FP-Diffusion: Improving Score-based Diffusion Models by Enforcing the Underlying Score Fokker-Planck Equation ICML 2023 From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks COLT 2023 Fully-Adaptive Composition in Differential Privacy ICML 2023 GANs as Gradient Flows that Converge JMLR 2023 Gaussian Processes on Distributions based on Regularized Optimal Transport AISTATS 2023 gDDIM: Generalized denoising diffusion implicit models ICLR 2023 Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels JMLR 2023 Generalization Error Bounds for Noisy, Iterative Algorithms via Maximal Leakage COLT 2023 Generator Identification for Linear SDEs with Additive and Multiplicative Noise NeurIPS 2023 GFlowNet Foundations JMLR 2023 GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration ICML 2023 Gradient-based Wang-Landau Algorithm: A Novel Sampler for Output Distribution of Neural Networks over the Input Space ICML 2023 Greedy Poisson Rejection Sampling NeurIPS 2023 Hawkes Process Based on Controlled Differential Equations IJCAI 2023 Hawkes Process with Flexible Triggering Kernels MLHC 2023 Hebbian and Gradient-based Plasticity Enables Robust Memory and Rapid Learning in RNNs ICLR 2023 Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation AISTATS 2023 Hidden Markov Transformer for Simultaneous Machine Translation ICLR 2023 High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance ICML 2023 High Probability Convergence of Stochastic Gradient Methods ICML 2023 HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation JMLR 2023