28 citations · 28 across the 9 of their papers we have counts for
10 papers
Bao: Automatic Region Placement and Memory Allocation for Intermittent Computing
Byeongjee Kang, Jan Hoffmann, Limin Jia +2
Intermittent computing enables batteryless embedded devices to operate in harsh environment, but frequent power failures interrupt program execution and require careful management…
Space-Entropy Lower Bounds for Random Sampling
Thomas L. Draper, Feras A. Saad
We prove fundamental space lower bounds for exact random sampling using an entropy source of i.i.d. uniform bits. A classic result from information theory shows that generating …
Online Random Sampling with Real Probabilities
Thomas L. Draper, David G. Harris, Feras A. Saad
We develop an efficient online algorithm to sample a sequence of discrete random variables using an entropy source of i.i.d. fair coin flips, in a standard model of real computatio…
GradInf: Gradient Estimation as Probabilistic Inference
Gaurav Arya, Mathieu Huot, Moritz Schauer +2
Gradient estimation -- the task of computing the gradient of the expected value of a probabilistic program -- has diverse applications in scientific computing, but is notoriously d…
Analyzing Decoders for Quantum Error Correction
Abtin Molavi, Feras Saad, Aws Albarghouthi
Quantum error correction (QEC) enables reliable computation on noisy hardware by encoding logical information across many physical qubits and periodically measuring parities to det…
Floating-Point Neural Networks Are Provably Robust Universal Approximators
Geonho Hwang, Wonyeol Lee, Yeachan Park +2
The classical universal approximation (UA) theorem for neural networks establishes mild conditions under which a feedforward neural network can approximate a continuous function $f…
Random Variate Generation with Formal Guarantees
Feras A. Saad, Wonyeol Lee
This article introduces a new approach to principled and practical random variate generation with formal guarantees. The key idea is to first specify the desired probability distri…
Efficient Online Random Sampling via Randomness Recycling
Thomas L. Draper, Feras A. Saad
This article studies the fundamental problem of using i.i.d. coin tosses from an entropy source to efficiently generate random variables , where $(P_1, P_…
Efficient Rejection Sampling in the Entropy-Optimal Range
Thomas L. Draper, Feras A. Saad
We study the problem of generating a random variate from a finite discrete probability distribution using an entropy source of independent fair coin flips. A classic result…
Scalable Spatiotemporal Prediction with Bayesian Neural Fields
Feras Saad, Jacob Burnim, Colin Carroll +4
Spatiotemporal datasets, which consist of spatially-referenced time series, are ubiquitous in diverse applications, such as air pollution monitoring, disease tracking, and cloud-de…