Search Results for author: Richie Yeung

Found 7 papers, 3 papers with code

A Pipeline For Discourse Circuits From CCG

no code implementations29 Nov 2023 Jonathon Liu, Razin A. Shaikh, Benjamin Rodatz, Richie Yeung, Bob Coecke

DisCoCirc represents natural language text as a `circuit' that captures the core semantic information of the text.


Differentiating and Integrating ZX Diagrams with Applications to Quantum Machine Learning

no code implementations31 Jan 2022 Quanlong Wang, Richie Yeung, Mark Koch

Here we elevate ZX to an analytical perspective by realising differentiation and integration entirely within the framework of ZX-calculus.

Quantum Machine Learning

A Quantum Natural Language Processing Approach to Musical Intelligence

2 code implementations10 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.

Representing and Implementing Matrices Using Algebraic ZX-calculus

2 code implementations13 Oct 2021 Quanlong Wang, Richie Yeung

In linear algebra applications, elementary matrices hold a significant role.

A CCG-Based Version of the DisCoCat Framework

no code implementations ACL (SemSpace, IWCS) 2021 Richie Yeung, Dimitri Kartsaklis

While the DisCoCat model (Coecke et al., 2010) has been proved a valuable tool for studying compositional aspects of language at the level of semantics, its strong dependency on pregroup grammars poses important restrictions: first, it prevents large-scale experimentation due to the absence of a pregroup parser; and second, it limits the expressibility of the model to context-free grammars.

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.

BIG-bench Machine Learning Quantum Machine Learning

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