8 citations · 8 across the 8 of their papers we have counts for
11 papers
Quantum-Enhanced Inference of Conditional Future Probabilities with Reduced Memory Cost
Jianjun Chen, Akshat Gupta, Chengran Yang +4
Many potential future events have devastating consequences, from the onset of earthquakes to financial black swan events. Accurate predictions of their probability of occurrence ar…
Robust -learning for mean-field control under Wasserstein uncertainty in common noise
Mathieu Laurière, Ariel Neufeld, Kyunghyun Park
In this article, we present a robust -learning algorithm for discrete-time mean-field control problems under Wasserstein uncertainty in the common noise law. The algorithm combi…
Robust mean-field control under common noise uncertainty
Mathieu Laurière, Ariel Neufeld, Kyunghyun Park
We propose and analyze a framework for discrete-time robust mean-field control problems under common noise uncertainty. In this framework, the mean-field interaction describes the…
Scaling limits of multi-period distributionally robust optimization problems
Max Nendel, Ariel Neufeld, Kyunghyun Park +1
We examine the scaling limit of multi-period distributionally robust optimization (DRO) problems via a semigroup approach. Each period involves a worst-case maximization over distr…
Provably convergent stochastic fixed-point algorithm for free-support Wasserstein barycenter of continuous non-parametric measures
Zeyi Chen, Ariel Neufeld, Qikun Xiang
We develop an estimator-based stochastic fixed-point framework for approximately computing the 2-Wasserstein barycenter of continuous, non-parametric probability measures. Notably,…
QuLTSF: Long-Term Time Series Forecasting with Quantum Machine Learning
Hari Hara Suthan Chittoor, Paul Robert Griffin, Ariel Neufeld +2
Long-term time series forecasting (LTSF) involves predicting a large number of future values of a time series based on the past values. This is an essential task in a wide range of…