3 citations · 7 across the 14 of their papers we have counts for
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Malliavin Calculus with Weak Derivatives for Counterfactual Stochastic Optimization
Vikram Krishnamurthy, Luke Snow
We study counterfactual stochastic optimization of conditional loss functionals under misspecified and noisy gradient information. The difficulty is that when the conditioning even…
Multi-Agent Inverse Reinforcement Learning for Identifying Pareto-Efficient Coordination -- A Distributionally Robust Approach
Luke Snow, Vikram Krishnamurthy
Multi-agent inverse reinforcement learning (IRL) aims to identify Pareto-efficient behavior in a multi-agent system, and reconstruct utility functions of the individual agents. Mot…
Multi-Agent Inverse Learning for Sensor Networks: Identifying Coordination in UAV Networks
Luke Snow, Vikram Krishnamurthy
Suppose there is an adversarial UAV network being tracked by a radar. How can the radar determine whether the UAVs are coordinating, in some well-defined sense? How can the radar i…
Efficient Neural SDE Training using Wiener-Space Cubature
Luke Snow, Vikram Krishnamurthy
A neural stochastic differential equation (SDE) is an SDE with drift and diffusion terms parametrized by neural networks. The training procedure for neural SDEs consists of optimiz…