Artifact for "DeGAS: Gradient-Based Optimization of Probabilistic Programs without Sampling"
Abstract
Artifact for replication of the experiments in the paper "DeGAS: Gradient-Based Optimization of Probabilistic Programs without Sampling", from Francesca Randone, Romina Doz, Mirco Tribastone and Luca Bortolussi.
Fields of Study & Subjects
Advanced Multi-Objective Optimization Algorithms
Stochastic Gradient Optimization Techniques
Gaussian Processes and Bayesian Inference
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 1 January 2026
- Document type
- Book