Stochastic Processes

Transport Elliptical Slice Sampling AISTATS 2023 Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach NeurIPS 2023 TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation AISTATS 2023 Understanding DDPM Latent Codes Through Optimal Transport ICLR 2023 Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles ICLR 2023 Unified Enhancement of Privacy Bounds for Mixture Mechanisms via f-Differential Privacy NeurIPS 2023 Uniform-in-time propagation of chaos for the mean-field gradient Langevin dynamics ICLR 2023 Universality of Langevin Diffusion for Private Optimization, with Applications to Sampling from Rashomon Sets COLT 2023 Universal Physics-Informed Neural Networks: Symbolic Differential Operator Discovery with Sparse Data ICML 2023 Unleashing the Power of Randomization in Auditing Differentially Private ML NeurIPS 2023 Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation NeurIPS 2023 Unveiling the sampling density in non-uniform geometric graphs ICLR 2023 Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms COLT 2023 Variance-Preserving-Based Interpolation Diffusion Models for Speech Enhancement Interspeech 2023 Variational Autoencoding Neural Operators ICML 2023 Variational Inference for Neyman-Scott Processes AISTATS 2023 Variational Inference with Gaussian Score Matching NeurIPS 2023 Variational Sparse Inverse Cholesky Approximation for Latent Gaussian Processes via Double Kullback-Leibler Minimization ICML 2023 VeCare: Statistical Acoustic Sensing for Automotive In-Cabin Monitoring NSDI 2023 Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints AISTATS 2023 What can online reinforcement learning with function approximation benefit from general coverage conditions? ICML 2023 What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variability EMNLP 2023 Why think step by step? Reasoning emerges from the locality of experience NeurIPS 2023 Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models NeurIPS 2023 A Continuous Time Framework for Discrete Denoising Models NeurIPS 2022