Forecasting Black Sigatoka Infection Risks with Latent Neural ODEs

1 code implementation • 1 Dec 2020 • Yuchen Wang, Matthieu Chan Chee, Ziyad Edher, Minh Duc Hoang, Shion Fujimori, Sornnujah Kathirgamanathan, Jesse Bettencourt

Black Sigatoka disease severely decreases global banana production, and climate change aggravates the problem by altering fungal species distributions.

Learning Differential Equations that are Easy to Solve

1 code implementation • NeurIPS 2020 • Jacob Kelly, Jesse Bettencourt, Matthew James Johnson, David Duvenaud

Differential equations parameterized by neural networks become expensive to solve numerically as training progresses.

Density Estimation Time Series +1

DiffEqFlux.jl - A Julia Library for Neural Differential Equations

5 code implementations • 6 Feb 2019 • Chris Rackauckas, Mike Innes, Yingbo Ma, Jesse Bettencourt, Lyndon White, Vaibhav Dixit

We show high-level functionality for defining neural ordinary differential equations (neural networks embedded into the differential equation) and describe the extra models in the Flux model zoo which includes neural stochastic differential equations.

BIG-bench Machine Learning

FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models

7 code implementations • ICLR 2019 • Will Grathwohl, Ricky T. Q. Chen, Jesse Bettencourt, Ilya Sutskever, David Duvenaud

The result is a continuous-time invertible generative model with unbiased density estimation and one-pass sampling, while allowing unrestricted neural network architectures.

Density Estimation Image Generation +1

Neural Ordinary Differential Equations

55 code implementations • NeurIPS 2018 • Ricky T. Q. Chen, Yulia Rubanova, Jesse Bettencourt, David Duvenaud

Instead of specifying a discrete sequence of hidden layers, we parameterize the derivative of the hidden state using a neural network.

Multivariate Time Series Forecasting Multivariate Time Series Imputation