Projects that are tagged with symbolic differentiation.


Logo Theano 1.0.2

by jaberg - May 23, 2018, 16:34:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 46422 views, 7824 downloads, 3 subscriptions

About: A Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Dynamically generates CPU and GPU modules for good performance. Deep Learning Tutorials illustrate deep learning with Theano.

Changes:

Theano 1.0.2 (23rd of May, 2018)

This is a maintenance release of Theano, version 1.0.2, with no new features, but some important bug fixes.

We recommend that everybody update to this version.

Highlights (since 1.0.1):

  • Theano should work under PyPy now (this is experimental).
  • Update for cuDNN 7.1 RNN API changes.
  • Fix for a crash related to mixed dtypes with cuDNN convolutions.
  • MAGMA should work in more cases without manual config.
  • Handle reductions with non-default accumulator dtype better on the GPU.
  • Improvements to the test suite so that it fails less often due to random chance.

A total of 6 people contributed to this release since 1.0.1:

  • Frederic Bastien
  • Steven Bocco
  • Jon Haygood
  • Arnaud Bergeron
  • Jordan Melendez
  • Desiree Vogt-Lee
  • Garming Sam
  • Pascal Lamblin
  • Vincent Dumoulin
  • Glexin
  • Simon Lefrancois

Logo DiffSharp 0.7.7

by gbaydin - January 4, 2016, 00:57:35 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 23547 views, 4303 downloads, 3 subscriptions

About: DiffSharp is a functional automatic differentiation (AD) library providing gradients, Hessians, Jacobians, directional derivatives, and matrix-free Hessian- and Jacobian-vector products as higher-order functions. It allows exact and efficient calculation of derivatives, with support for nesting.

Changes:

Fixed: Bug fix in forward AD implementation of Sigmoid and ReLU for D, DV, and DM (fixes #16, thank you @mrakgr)

Improvement: Performance improvement by removing several more Parallel.For and Array.Parallel.map operations, working better with OpenBLAS multithreading

Added: Operations involving incompatible dimensions of DV and DM will now throw exceptions for warning the user