| Bounding adapted Wasserstein metrics J Blanchet, M Larsson, J Park, J Wiesel arXiv preprint arXiv:2407.21492, 2024 | | 2024 |
| Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions P Kuiper, A Hasan, W Yang, Y Ng, H Bidkhori, J Blanchet, V Tarokh arXiv preprint arXiv:2408.00131, 2024 | | 2024 |
| Generative Learning for Simulation of US Army Vehicle Faults P Kuiper, S Lin, J Blanchet, V Tarokh arXiv preprint arXiv:2407.17654, 2024 | | 2024 |
| Optimization under rare events: scaling laws for linear chance-constrained programs J Blanchet, J Jorritsma, B Zwart arXiv preprint arXiv:2407.11825, 2024 | | 2024 |
| An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations S Wang, J Blanchet, P Glynn arXiv preprint arXiv:2407.10065, 2024 | 1 | 2024 |
| ScoreFusion: fusing score-based generative models via Kullback-Leibler barycenters H Liu, J Blanchet, N Si arXiv preprint arXiv:2406.19619, 2024 | | 2024 |
| Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces S Wang, N Si, J Blanchet, Z Zhou arXiv preprint arXiv:2406.11281, 2024 | | 2024 |
| Modeling shortest paths in polymeric networks using spatial branching processes Z Zhang, S Mohanty, J Blanchet, W Cai Journal of the Mechanics and Physics of Solids 187, 105636, 2024 | 3 | 2024 |
| Deep Learning for Computing Convergence Rates of Markov Chains Y Qu, J Blanchet, P Glynn arXiv preprint arXiv:2405.20435, 2024 | | 2024 |
| Provably mitigating overoptimization in rlhf: Your sft loss is implicitly an adversarial regularizer Z Liu, M Lu, S Zhang, B Liu, H Guo, Y Yang, J Blanchet, Z Wang arXiv preprint arXiv:2405.16436, 2024 | 3 | 2024 |
| Consistency of Neural Causal Partial Identification J Tan, J Blanchet, V Syrgkanis arXiv preprint arXiv:2405.15673, 2024 | | 2024 |
| Stability Evaluation via Distributional Perturbation Analysis J Blanchet, P Cui, J Li, J Liu arXiv preprint arXiv:2405.03198, 2024 | | 2024 |
| Fair neural networks X Hua, H Xu, J Blanchet, VA Nguyen, MPG Castro US Patent App. 18/051,578, 2024 | | 2024 |
| Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty K Liu, J Blanchet, L Ying, Y Lu arXiv preprint arXiv:2404.19145, 2024 | | 2024 |
| Feasible -Learning for Average Reward Reinforcement Learning Y Jin, R Gummadi, Z Zhou, J Blanchet International Conference on Artificial Intelligence and Statistics, 1630-1638, 2024 | | 2024 |
| On the First Passage Times of Branching Random Walks in J Blanchet, W Cai, S Mohanty, Z Zhang arXiv preprint arXiv:2404.09064, 2024 | | 2024 |
| Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm M Lu, H Zhong, T Zhang, J Blanchet arXiv preprint arXiv:2404.03578, 2024 | | 2024 |
| When are Unbiased Monte Carlo Estimators More Preferable than Biased Ones? G Wang, J Blanchet, PW Glynn arXiv preprint arXiv:2404.01431, 2024 | 1 | 2024 |
| Sample-path large deviations for unbounded additive functionals of the reflected random walk M Bazhba, J Blanchet, CH Rhee, B Zwart Mathematics of Operations Research, 2024 | 3 | 2024 |
| Automatic outlier rectification via optimal transport J Blanchet, J Li, M Pelger, G Zanotti arXiv preprint arXiv:2403.14067, 2024 | 3 | 2024 |
Peter W. GlynnProfessor of Management Science and EngineeringVerified email at stanford.edu