Publications associées à Grammaire générative et transformationnelle

Fashioning Creative Expertise with Generative AI: Graphical Interfaces for GAN-Based Design Space Exploration Better Support Ideation Than Text Prompts for Diffusion Models

Pierre Dillenbourg, Richard Lee Davis, Tanja Christina Käser Jacober, Kevin Gonyop Kim, Wei Jiang, Thiemo Wambsganss

This paper investigates the potential impact of deep generative models on the work of creative professionals. We argue that current generative modeling tools lack critical features that would make them useful creativity support tools, and introduce our own ...

2024

Multiscale pattern analysis of building replacements in Zurich from 2000 to 2019

Corentin Jean Dominique Fivet, Jingxian Ye

Building replacement (BR) – i.e., the demolition of existing structures and subsequent construction of new buildings on the same site – is often understood as a necessary urban planning strategy despite significant environmental implications regarding soli ...

2023

Event-related causality in stereo-EEG discriminates syntactic processing of noun phrases and verb phrases

Silvestro Micera, Fiorenzo Artoni

Objective. Syntax involves complex neurobiological mechanisms, which are difficult to disentangle for multiple reasons. Using a protocol able to separate syntactic information from sound information we investigated the neural causal connections evoked by t ...

IOP Publishing Ltd2023

GANs for All: Supporting Fun and Intuitive Exploration of GAN Latent Spaces

Pierre Dillenbourg, Richard Lee Davis, Kevin Gonyop Kim, Wei Jiang

We have developed a new tool that makes it possible for people with zero programming experience to intentionally and meaningfully explore the latent space of a GAN. We combine a number of methods from the literature into a single system that includes multi ...

PMLR2022

DeepNC: Deep Generative Network Completion

Andreas Oliver Spitz

Most network data are collected from partially observable networks with both missing nodes and missing edges, for example, due to limited resources and privacy settings specified by users on social media. Thus, it stands to reason that inferring the missin ...

IEEE COMPUTER SOC2022

Grammar-based generation of bar networks in static equilibrium with bounded bar lengths

Corentin Jean Dominique Fivet, Ioannis Mirtsopoulos

This paper presents a generative approach for the conceptual design of structures, which aims at exploring alternative bar networks in static equilibrium by means of a grammar rule. Operating on incomplete networks of bars in interim static equilibrium, th ...

2021

Gramatron: Effective Grammar-Aware Fuzzing

Mathias Josef Payer

Fuzzers aware of the input grammar can explore deeper program states using grammar-aware mutations. Existing grammar-aware fuzzers are ineffective at synthesizing complex bug triggers due to: (i) grammars introducing a sampling bias during input generation ...

ASSOC COMPUTING MACHINERY2021

The Learnability of the Grammar of Jazz: Bayesian Inference of Hierarchical Structures in Harmony

Daniel Harasim

Musical grammar describes a set of principles that are used to understand and interpret the structure of a piece according to a musical style. The main topic of this study is grammar induction for harmony --- the process of learning structural principles f ...

EPFL2020

Harmonic Syntax in Time: Rhythm Improves Grammatical Models of Harmony

Martin Alois Rohrmeier, Daniel Harasim

Music is hierarchically structured, both in how it is perceived by listeners and how it is composed. Such structure can be elegantly captured using probabilistic grammatical models similar to those used to study natural language. They address the complexit ...

ISMIR2019

Structural Rewriting in XOR-Majority Graphs

Giovanni De Micheli, Mathias Soeken, Zhufei Chu

In this paper, we present a structural rewriting method for a recently proposed XOR-Majority graph (XMG), which has exclusive-OR (XOR), majority-of-three (MAJ), and inverters as primitives. XMGs are an extension of Majority-Inverter Graphs (MIGs). Previous ...

ASSOC COMPUTING MACHINERY2019