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Order by: [Title], [Author], [Editor], [Year]
Audrunas Gruslys, Remi Munos, Ivo Danihelka, Marc Lanctot, Alex Graves
Memory-Efficient Backpropagation Through Time
Advances in Neural Information Processing Systems 29, Curran Associates, Inc., 2016
Theory & Techniques:
Checkpointing
Sham M. Kakade, Jason D. Lee
Provably Correct Automatic Sub-Differentiation for Qualified Programs
Conference proceeding, Advances in Neural Information Processing Systems, Curran Associates, Inc., 2018
Theory & Techniques:
Generalized Subderivatives
Soeren Laue, Matthias Mitterreiter, Joachim Giesen
Computing Higher Order Derivatives of Matrix and Tensor Expressions
Conference proceeding, Advances in Neural Information Processing Systems, Curran Associates, Inc., 2018
Theory & Techniques:
Hierarchical Approach
van Merriënboer, Bart, Dan Moldovan, Alexander Wiltschko
Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming
Conference proceeding, Advances in Neural Information Processing Systems, Curran Associates, Inc., 2018
Tools:
Tangent
van Merriënboer, Bart, Olivier Breuleux, Arnaud Bergeron, Pascal Lamblin
Automatic differentiation in ML: Where we are and where we should be going
Conference proceeding, Advances in Neural Information Processing Systems, Curran Associates, Inc., 2018
Theory & Techniques:
General, Implementation Strategies

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