activity
20172026
most citedArray Languages Make Neural Networks Fast

5 citations · 12 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LO2026

When Agda met Vampire

Artjoms Šinkarovs, Michael Rawson

Dependently-typed proof assistants furnish expressive foundations for mechanised mathematics and verified software. However, automation for these systems has been either modest in…

cs.PL2025

Comparing Parallel Functional Array Languages: Programming and Performance

David van Balen, Tiziano De Matteis, Clemens Grelck +12

Parallel functional array languages are an emerging class of programming languages that promise to combine low-effort parallel programming with good performance and performance por…

cs.PL2025★ 1 cited

Neural Network Verification is a Programming Language Challenge

Lucas C. Cordeiro, Matthew L. Daggitt, Julien Girard-Satabin +8

Neural network verification is a new and rapidly developing field of research. So far, the main priority has been establishing efficient verification algorithms and tools, while pr…

cs.PL2024★ 1 cited

Correctness is Demanding, Performance is Frustrating

Artjoms Sinkarovs, Thomas Koopman, Sven-Bodo Scholz

In this paper we demonstrate a technique for developing high performance applications with strong correctness guarantees. We use a theorem prover to derive a high-level specificati…

cs.PL2021★ 1 cited

Choosing is Losing: How to combine the benefits of shallow and deep embeddings through reflection

Artjoms Šinkarovs, Jesper Cockx

Dependently-typed host languages empower users to verify a wide range of properties of embedded languages and programs written in them. Designers of such embedded languages are fac…

cs.DS2020★ 2 cited

Multi-dimensional Arrays with Levels

Artjoms {Š}inkarovs

We explore a data structure that generalises rectangular multi-dimensional arrays. The shape of an n-dimensional array is typically given by a tuple of n natural numbers. Each elem…

cs.PL2019★ 5 cited

Array Languages Make Neural Networks Fast

Artjoms Šinkarovs, Hans-Nikolai Vießmann, Sven-Bodo Scholz

Modern machine learning frameworks are complex: they are typically organised in multiple layers each of which is written in a different language and they depend on a number of exte…

cs.PL2017★ 2 cited

A Lambda Calculus for Transfinite Arrays: Unifying Arrays and Streams

Artjoms Sinkarovs, Sven-Bodo Scholz

Array programming languages allow for concise and generic formulations of numerical algorithms, thereby providing a huge potential for program optimisation such as fusion, parallel…