1 code implementation • 8 Oct 2021 • Dimitri Kartsaklis, Ian Fan, Richie Yeung, Anna Pearson, Robin Lorenz, Alexis Toumi, Giovanni De Felice, Konstantinos Meichanetzidis, Stephen Clark, Bob Coecke
We present lambeq, the first high-level Python library for Quantum Natural Language Processing (QNLP).
2 code implementations • 10 Nov 2021 • Eduardo Reck Miranda, Richie Yeung, Anna Pearson, Konstantinos Meichanetzidis, Bob Coecke
In particular, we are importing methods from the Distributional Compositional Categorical (DisCoCat) modelling framework for Natural Language Processing (NLP), motivated by musical grammars.
3 code implementations • 25 Feb 2021 • Robin Lorenz, Anna Pearson, Konstantinos Meichanetzidis, Dimitri Kartsaklis, Bob Coecke
Our aim in doing this is to take the first small steps in this unexplored research territory and pave the way for practical Quantum Natural Language Processing.
1 code implementation • 7 Dec 2020 • Bob Coecke, Giovanni De Felice, Konstantinos Meichanetzidis, Alexis Toumi
We recall how the quantum model for natural language that we employ canonically combines linguistic meanings with rich linguistic structure, most notably grammar.
1 code implementation • 17 May 2019 • Giovanni de Felice, Konstantinos Meichanetzidis, Alexis Toumi
Distributional compositional (DisCo) models are functors that compute the meaning of a sentence from the meaning of its words.
no code implementations • 3 Jan 2020 • Bob Coecke, Konstantinos Meichanetzidis
This result is of interest to quantum foundations, as it bridges the work in Categorical Quantum Mechanics (CQM) with that on conditional quantum states.
no code implementations • 8 May 2020 • Konstantinos Meichanetzidis, Stefano Gogioso, Giovanni de Felice, Nicolò Chiappori, Alexis Toumi, Bob Coecke
In this work, we describe a full-stack pipeline for natural language processing on near-term quantum computers, aka QNLP.
no code implementations • 7 Dec 2020 • Konstantinos Meichanetzidis, Alexis Toumi, Giovanni De Felice, Bob Coecke
In this work, we focus on the capabilities of noisy intermediate-scale quantum (NISQ) hardware and perform the first implementation of an NLP task on a NISQ processor, using the DisCoCat framework.
no code implementations • 2 Jul 2021 • Bob Coecke, Giovanni De Felice, Konstantinos Meichanetzidis, Alexis Toumi
This is a story about making quantum computers speak, and doing so in a quantum-native, compositional and meaning-aware manner.
no code implementations • 10 Dec 2021 • Péter Mernyei, Konstantinos Meichanetzidis, İsmail İlkan Ceylan
We investigate quantum circuits for graph representation learning, and propose equivariant quantum graph circuits (EQGCs), as a class of parameterized quantum circuits with strong relational inductive bias for learning over graph-structured data.
1 code implementation • 27 Nov 2023 • Charles London, Douglas Brown, Wenduan Xu, Sezen Vatansever, Christopher James Langmead, Dimitri Kartsaklis, Stephen Clark, Konstantinos Meichanetzidis
By constructing quantum models based on parameterised quantum circuits we perform sequence classification on a task relevant to the design of therapeutic proteins, and find competitive performance with classical baselines of similar scale.
no code implementations • 22 Feb 2024 • Francisco J. R. Ruiz, Tuomas Laakkonen, Johannes Bausch, Matej Balog, Mohammadamin Barekatain, Francisco J. H. Heras, Alexander Novikov, Nathan Fitzpatrick, Bernardino Romera-Paredes, John van de Wetering, Alhussein Fawzi, Konstantinos Meichanetzidis, Pushmeet Kohli
A key challenge in realizing fault-tolerant quantum computers is circuit optimization.