Search Results for author: Giovanni De Felice

Found 10 papers, 4 papers with code

How to make qubits speak

no code implementations2 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.

Question Answering

Diagrammatic Differentiation for Quantum Machine Learning

no code implementations14 Mar 2021 Alexis Toumi, Richie Yeung, Giovanni De Felice

We introduce diagrammatic differentiation for tensor calculus by generalising the dual number construction from rigs to monoidal categories.

Quantum Machine Learning

Foundations for Near-Term Quantum Natural Language Processing

no code implementations7 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.

Grammar-Aware Question-Answering on Quantum Computers

no code implementations7 Dec 2020 Konstantinos Meichanetzidis, Alexis Toumi, Giovanni De Felice, Bob Coecke

Natural language processing (NLP) is at the forefront of great advances in contemporary AI, and it is arguably one of the most challenging areas of the field.

Question Answering

Functorial Language Games for Question Answering

1 code implementation19 May 2020 Giovanni de Felice, Elena Di Lavore, Mario Román, Alexis Toumi

We present some categorical investigations into Wittgenstein's language-games, with applications to game-theoretic pragmatics and question-answering in natural language processing.

Question Answering

Quantum Natural Language Processing on Near-Term Quantum Computers

no code implementations8 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.

Language Modelling Quantum Machine Learning

DisCoPy: Monoidal Categories in Python

2 code implementations6 May 2020 Giovanni de Felice, Alexis Toumi, Bob Coecke

We introduce DisCoPy, an open source toolbox for computing with monoidal categories.

Category Theory

Functorial Question Answering

1 code implementation17 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.

Question Answering

Towards Compositional Distributional Discourse Analysis

no code implementations8 Nov 2018 Bob Coecke, Giovanni De Felice, Dan Marsden, Alexis Toumi

Categorical compositional distributional semantics provide a method to derive the meaning of a sentence from the meaning of its individual words: the grammatical reduction of a sentence automatically induces a linear map for composing the word vectors obtained from distributional semantics.

Language understanding Natural Language Understanding +1

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