Stochastic Processes

On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models ICLR 2024 Online non-parametric likelihood-ratio estimation by Pearson-divergence functional minimization AISTATS 2024 On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic Choices EMNLP 2024 On the Computational Complexity of Metropolis-Adjusted Langevin Algorithms for Bayesian Posterior Sampling JMLR 2024 On the Convergence of Loss and Uncertainty-based Active Learning Algorithms NeurIPS 2024 On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory NeurIPS 2024 On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control JMLR 2024 On Unbiased Estimation for Partially Observed Diffusions JMLR 2024 Optimal-state Dynamics Estimation for Physics-based Human Motion Capture from Videos NeurIPS 2024 Optimizing Local Satisfaction of Long-Run Average Objectives in Markov Decision Processes AAAI 2024 Outlier-Robust Distributionally Robust Optimization via Unbalanced Optimal Transport NeurIPS 2024 Parallel-in-Time Probabilistic Numerical ODE Solvers JMLR 2024 Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent NeurIPS 2024 Paraphrase and Solve: Exploring and Exploiting the Impact of Surface Form on Mathematical Reasoning in Large Language Models NAACL 2024 Partial observation can induce mechanistic mismatches in data-constrained models of neural dynamics NeurIPS 2024 Particle Semi-Implicit Variational Inference NeurIPS 2024 Performative Control for Linear Dynamical Systems NeurIPS 2024 Physics-constrained learning of PDE systems with uncertainty quantified port-Hamiltonian models L4DC 2024 Physics-informed Neural Networks with Unknown Measurement Noise L4DC 2024 POAM: Probabilistic Online Attentive Mapping for Efficient Robotic Information Gathering RSS 2024 Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks JMLR 2024 Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel ICLR 2024 Practical Bayesian Algorithm Execution via Posterior Sampling NeurIPS 2024 PRASS: Probabilistic Risk-averse Robust Learning with Stochastic Search IJCAI 2024 Predicting the Unpredictable: Uncertainty-Aware Reasoning over Temporal Knowledge Graphs via Diffusion Process ACL 2024