16 citations · 18 across the 12 of their papers we have counts for
13 papers
Well-Posed KL-Regularized Control via Wasserstein and Kalman-Wasserstein KL Divergences
Viktor Stein, Adwait Datar, Nihat Ay
Kullback-Leibler (KL) divergence regularization is widely used in reinforcement learning, but it becomes infinite under support mismatch and can degenerate in low-noise regimes. Us…
Convergence Properties of Natural Gradient Descent for Minimizing KL Divergence
Adwait Datar, Nihat Ay
The Kullback-Leibler (KL) divergence plays a central role in probabilistic machine learning, where it commonly serves as the canonical loss function. Optimization in such settings…
Information Geometry for Wasserstein KL Divergence of Gaussian Measures on
Adwait Datar, Nihat Ay
We study the Wasserstein Kullback--Leibler divergence (WKL divergence) on the manifold of nondegenerate Gaussian measures over . In the canonical-divergence constructi…
Robust Stability for Multiagent Systems with Spatio-Temporally Correlated Packet Loss
Christian Hespe, Adwait Datar, Herbert Werner
A problem with considering correlations in the analysis of multiagent system with stochastic packet loss is that they induce dependencies between agents that are otherwise decouple…
Systematic construction of continuous-time neural networks for linear dynamical systems
Chinmay Datar, Adwait Datar, Felix Dietrich +1
Discovering a suitable neural network architecture for modeling complex dynamical systems poses a formidable challenge, often involving extensive trial and error and navigation thr…
Transformation-Free Fixed-Structure Model Reduction for LPV Systems
Lennart Heeren, Adwait Datar, Antonio Mendez Gonzalez +1
In this paper, we propose a model reduction technique for linear parameter varying (LPV) systems based on available tools for fixed-structure controller synthesis. We start by tran…