1 citations · 2 across the 9 of their papers we have counts for
9 papers
Efficient Distribution Learning with Error Bounds in Wasserstein Distance
Eduardo Figueiredo, Steven Adams, Luca Laurenti
The Wasserstein distance has emerged as a key metric to quantify distances between probability distributions, with applications in various fields, including machine learning, contr…
discretize_distributions: Efficient Quantization of Gaussian Mixtures with Guarantees in Wasserstein Distance
Steven Adams, Elize Alwash, Luca Laurenti
We present discretize_distributions, a Python package that efficiently constructs discrete approximations of Gaussian mixture distributions and provides guarantees on the approxima…
Efficient Uncertainty Propagation with Guarantees in Wasserstein Distance
Eduardo Figueiredo, Steven Adams, Peyman Mohajerin Esfahani +1
In this paper, we consider the problem of propagating an uncertain distribution by a possibly non-linear function and quantifying the resulting uncertainty. We measure the uncertai…
Formal Uncertainty Propagation for Stochastic Dynamical Systems with Additive Noise
Steven Adams, Eduardo Figueiredo, Luca Laurenti
In this paper, we consider discrete-time non-linear stochastic dynamical systems with additive process noise in which both the initial state and noise distributions are uncertain.…
Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection
Steven Adams, Andrea Patanè, Morteza Lahijanian +1
Infinitely wide or deep neural networks (NNs) with independent and identically distributed (i.i.d.) parameters have been shown to be equivalent to Gaussian processes. Because of th…
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming
Steven Adams, Andrea Patane, Morteza Lahijanian +1
In this paper, we introduce BNN-DP, an efficient algorithmic framework for analysis of adversarial robustness of Bayesian Neural Networks (BNNs). Given a compact set of input point…
CANE: A Cascade-Control Approach for Network-Assisted Video QoE Management
Mehdi Hosseinzadeh, Karthick Shankar, Maria Apostolaki +4
Prior efforts have shown that network-assisted schemes can improve the Quality-of-Experience (QoE) and QoE fairness when multiple video players compete for bandwidth. However, real…
Formal Control Synthesis for Stochastic Neural Network Dynamic Models
Steven Adams, Morteza Lahijanian, Luca Laurenti
Neural networks (NNs) are emerging as powerful tools to represent the dynamics of control systems with complicated physics or black-box components. Due to complexity of NNs, howeve…
A Self-Guided Approach for Navigation in a Minimalistic Foraging Robotic Swarm
Steven Adams, Daniel Jarne Ornia, Manuel Mazo
We present a biologically inspired design for swarm foraging based on ant's pheromone deployment, where the swarm is assumed to have very restricted capabilities. The robots do not…