Storchastic: A Framework for General Stochastic Automatic Differentiation

1 April 2021

Papers citing "Storchastic: A Framework for General Stochastic Automatic Differentiation"

5 / 5 papers shown

Title
Branches of a Tree: Taking Derivatives of Programs with Discrete and Branching Randomness in High Energy Physics Michael Kagan Lukas Heinrich 29 9 0 31 Aug 2023
Automatic Differentiation of Programs with Discrete Randomness Gaurav Arya Moritz Schauer Frank Schafer Chris Rackauckas 23 34 0 16 Oct 2022
Sparse Graph Learning from Spatiotemporal Time Series Andrea Cini Daniele Zambon Cesare Alippi CML AI4TS 40 18 0 26 May 2022
Direct Evolutionary Optimization of Variational Autoencoders With Binary Latents E. Guiraud Jakob Drefs Jörg Lücke DRL 33 3 0 27 Nov 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 338 11,684 0 09 Mar 2017