3 citations · 5 across the 7 of their papers we have counts for
8 papers
NP-LEAP: Nonparametric Latent Exchangeability Prior for Model-Lean Borrowing from Historical Data
Ethan M. Alt, Miheer Dewaskar, Jacob M. Maronge +2
Bayesian dynamic borrowing (BDB) methods leverage historical data to reduce treatment effect uncertainty, yet existing approaches rely on parametric outcome models susceptible to m…
Bayesian Level Set Clustering
David Buch, Miheer Dewaskar, David B. Dunson
Classically, Bayesian clustering interprets each component of a mixture model as a cluster. The inferred clustering posterior is highly sensitive to any inaccuracies in the kernel…
Robustifying likelihoods by optimistically re-weighting data
Miheer Dewaskar, Christopher Tosh, Jeremias Knoblauch +1
Likelihood-based inferences have been remarkably successful in wide-spanning application areas. However, even after due diligence in selecting a good model for the data at hand, th…
NExG: Provable and Guided State Space Exploration of Neural Network Control Systems using Sensitivity Approximation
Manish Goyal, Miheer Dewaskar, Parasara Sridhar Duggirala
We propose a new technique for performing state space exploration of closed loop control systems with neural network feedback controllers. Our approach involves approximating the s…
Finding Groups of Cross-Correlated Features in Bi-View Data
Miheer Dewaskar, John Palowitch, Mark He +2
Datasets in which measurements of two (or more) types are obtained from a common set of samples arise in many scientific applications. A common problem in the exploratory analysis…
Near Equilibrium Fluctuations for Supermarket Models with Growing Choices
Shankar Bhamidi, Amarjit Budhiraja, Miheer Dewaskar
We consider the supermarket model in the usual Markovian setting where jobs arrive at rate for some , with parallel servers each processing jobs in its queue a…
Controlling a population
Nathalie Bertrand, Miheer Dewaskar, Blaise Genest +2
We introduce a new setting where a population of agents, each modelled by a finite-state system, are controlled uniformly: the controller applies the same action to every agent. Th…
Controlling a Population
Nathalie Bertrand, Miheer Dewaskar, Blaise Genest +1
We introduce a new setting where a population of agents, each modelled by a finite-state system, are controlled uniformly: the controller applies the same action to every agent. Th…