Media Summary: Want to train programs to optimize themselves? Presenter: Gordon Plotkin Presented at POPL'2020. Boeing Distinguished Colloquium, November 21, 2019 Alan Edelman Massachusetts Institute of Technology Title: Julia: ...

The Principles Behind Differentiable Programming - Detailed Analysis & Overview

Want to train programs to optimize themselves? Presenter: Gordon Plotkin Presented at POPL'2020. Boeing Distinguished Colloquium, November 21, 2019 Alan Edelman Massachusetts Institute of Technology Title: Julia: ... Derivatives are at the heart of scientific Scientific computing is increasingly incorporating the advancements in machine learning and the ability to work with large ... In Fall 2020 and Spring 2021, this was MIT's 18.337J/6.338J: Parallel Computing and Scientific Machine Learning course.

e-Seminar on Scientific Machine Learning Speaker: Dr. Jan Drgona (PNNL) Abstract: In this talk, we will present a Talk from HSF/IRIS-HEP Analysis Ecosystem 2 Workshop ( Dimitri spittoon it is and Simon Peter Jones on This video was recorded at Scala Days Berlin 2018 Follow us on Twitter or visit our website for more information ...

Photo Gallery

The principles behind Differentiable Programming - Erik Meijer
What is Differentiable Programming
A Simple Differentiable Programming Language
Boeing Colloquium: Julia: Differentiable Programming and Software 2.0
Differentiable Programming (Part 1)
Models as Code: Differentiable Programming with Zygote
Differentiable Programming with Julia by Mike Innes
Differentiable Programming Part 1: Reverse-Mode AD Implementation
Differentiable Programming for Modeling and Control of Dynamical Systems
Differentiable Programming in HEP
Efficient Differentiable Programming in a Functional Array Processing Language
Differentiable Functional Programming by Noel Welsh
View Detailed Profile
The principles behind Differentiable Programming - Erik Meijer

The principles behind Differentiable Programming - Erik Meijer

Behind

What is Differentiable Programming

What is Differentiable Programming

Want to train programs to optimize themselves?

A Simple Differentiable Programming Language

A Simple Differentiable Programming Language

Presenter: Gordon Plotkin Presented at POPL'2020.

Boeing Colloquium: Julia: Differentiable Programming and Software 2.0

Boeing Colloquium: Julia: Differentiable Programming and Software 2.0

Boeing Distinguished Colloquium, November 21, 2019 Alan Edelman Massachusetts Institute of Technology Title: Julia: ...

Differentiable Programming (Part 1)

Differentiable Programming (Part 1)

Derivatives are at the heart of scientific

Models as Code: Differentiable Programming with Zygote

Models as Code: Differentiable Programming with Zygote

Scientific computing is increasingly incorporating the advancements in machine learning and the ability to work with large ...

Differentiable Programming with Julia by Mike Innes

Differentiable Programming with Julia by Mike Innes

We've discussed the idea of

Differentiable Programming Part 1: Reverse-Mode AD Implementation

Differentiable Programming Part 1: Reverse-Mode AD Implementation

In Fall 2020 and Spring 2021, this was MIT's 18.337J/6.338J: Parallel Computing and Scientific Machine Learning course.

Differentiable Programming for Modeling and Control of Dynamical Systems

Differentiable Programming for Modeling and Control of Dynamical Systems

e-Seminar on Scientific Machine Learning Speaker: Dr. Jan Drgona (PNNL) Abstract: In this talk, we will present a

Differentiable Programming in HEP

Differentiable Programming in HEP

Talk from HSF/IRIS-HEP Analysis Ecosystem 2 Workshop (https://indico.cern.ch/event/1125222/).

Efficient Differentiable Programming in a Functional Array Processing Language

Efficient Differentiable Programming in a Functional Array Processing Language

Dimitri spittoon it is and Simon Peter Jones on

Differentiable Functional Programming by Noel Welsh

Differentiable Functional Programming by Noel Welsh

This video was recorded at Scala Days Berlin 2018 Follow us on Twitter @ScalaDays or visit our website for more information ...

The impact of differentiable programming: how ∂P is enabling new science in Julia

The impact of differentiable programming: how ∂P is enabling new science in Julia

Fully incorporating