Matthijs Vákár

According to our database, Matthijs Vákár authored at least 26 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Efficient CHAD.

Tom Smeding, Matthijs Vákár

Proc. ACM Program. Lang., January, 2024

Free Doubly-Infinitary Distributive Categories are Cartesian Closed.

Fernando Lucatelli Nunes, Matthijs Vákár

CoRR, 2024

2023

Efficient Dual-Numbers Reverse AD via Well-Known Program Transformations.

Tom Smeding, Matthijs Vákár

Proc. ACM Program. Lang., January, 2023

CHAD for expressive total languages.

Fernando Lucatelli Nunes, Matthijs Vákár

Math. Struct. Comput. Sci., 2023

2022

CHAD: Combinatory Homomorphic Automatic Differentiation.

Matthijs Vákár, Tom Smeding

ACM Trans. Program. Lang. Syst., 2022

Conditional Independence by Typing.

Maria I. Gorinova, Andrew D. Gordon, Charles Sutton, Matthijs Vákár

ACM Trans. Program. Lang. Syst., 2022

Higher Order Automatic Differentiation of Higher Order Functions.

Mathieu Huot, Sam Staton, Matthijs Vákár

Log. Methods Comput. Sci., 2022

Logical Relations for Partial Features and Automatic Differentiation Correctness.

Fernando Lucatelli Nunes, Matthijs Vákár

CoRR, 2022

Automatic Differentiation for ML-family languages: correctness via logical relations.

Fernando Lucatelli Nunes, Matthijs Vákár

CoRR, 2022

Dual-Numbers Reverse AD, Efficiently.

Tom Smeding, Matthijs Vákár

CoRR, 2022

2021

CHAD: Combinatory Homomorphic Automatic Differentiation.

Matthijs Vákár

CoRR, 2021

Reverse AD at Higher Types: Pure, Principled and Denotationally Correct.

Matthijs Vákár

Proceedings of the Programming Languages and Systems, 2021

2020

Denotational Correctness of Foward-Mode Automatic Differentiation for Iteration and Recursion.

Matthijs Vákár

CoRR, 2020

Correctness of Automatic Differentiation via Diffeologies and Categorical Gluing.

Mathieu Huot, Sam Staton, Matthijs Vákár

Proceedings of the Foundations of Software Science and Computation Structures, 2020

Transforming Probabilistic Programs for Model Checking.

Ryan Bernstein, Matthijs Vákár, Jeannette M. Wing

Proceedings of the FODS '20: ACM-IMS Foundations of Data Science Conference, 2020

2019

A domain theory for statistical probabilistic programming.

Matthijs Vákár, Ohad Kammar, Sam Staton

Proc. ACM Program. Lang., 2019

2018

Denotational validation of higher-order Bayesian inference.

Adam Scibior, Ohad Kammar, Matthijs Vákár, Sam Staton, Hongseok Yang, Yufei Cai, Klaus Ostermann, Sean K. Moss, Chris Heunen, Zoubin Ghahramani

Proc. ACM Program. Lang., 2018

Game semantics for dependent types.

Matthijs Vákár, Radha Jagadeesan, Samson Abramsky

Inf. Comput., 2018

2017

In search of effectful dependent types.

Matthijs Vákár

PhD thesis, 2017

In Search of Effectful Dependent Types.

Matthijs Vákár

CoRR, 2017

Interpreting Lion Behaviour as Probabilistic Programs.

Neil Dhir, Matthijs Vákár, Matthew Wijers, Andrew Markham, Frank D. Wood

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

2016

An Effectful Treatment of Dependent Types.

Matthijs Vákár

CoRR, 2016

2015

A Framework for Dependent Types and Effects.

Matthijs Vákár

CoRR, 2015

Games for Dependent Types.

Samson Abramsky, Radha Jagadeesan, Matthijs Vákár

Proceedings of the Automata, Languages, and Programming - 42nd International Colloquium, 2015

A Categorical Semantics for Linear Logical Frameworks.

Matthijs Vákár

Proceedings of the Foundations of Software Science and Computation Structures, 2015

2014

Syntax and Semantics of Linear Dependent Types.

Matthijs Vákár

CoRR, 2014