activity
20232026
most citedMulti-Objective Quality-Diversity for Crystal Structure Prediction

5 citations · 9 across the 8 of their papers we have counts for

collaborators

9 papers

cs.LG2026

Uncovering the Generative Landscape of Diffusion Models: A Spectral-Guided Quality-Diversity Diffusion Framework

Hannah Janmohamed, Joao Correia, Penousal Machado +1

Denoising Diffusion Probabilistic Models have emerged as powerful generative priors across domains ranging from molecular design to high-resolution image synthesis. However, standa…

cs.NE2025

Time to Play: Simulating Early-Life Animal Dynamics Enhances Robotics Locomotion Discovery

Paul Templier, Hannah Janmohamed, David Labonte +1

Developmental changes in body morphology profoundly shape locomotion in animals, yet artificial agents and robots are typically trained under static physical parameters. Inspired b…

cs.LG2025

Multi-Objective Quality-Diversity in Unstructured and Unbounded Spaces

Hannah Janmohamed, Antoine Cully

Quality-Diversity algorithms are powerful tools for discovering diverse, high-performing solutions. Recently, Multi-Objective Quality-Diversity (MOQD) extends QD to problems with s…

cs.NE2025★ 1 cited

Dominated Novelty Search: Rethinking Local Competition in Quality-Diversity

Ryan Bahlous-Boldi, Maxence Faldor, Luca Grillotti +4

Quality-Diversity is a family of evolutionary algorithms that generate diverse, high-performing solutions through local competition principles inspired by natural evolution. While…

cs.AI2024

Preference-Conditioned Gradient Variations for Multi-Objective Quality-Diversity

Hannah Janmohamed, Maxence Faldor, Thomas Pierrot +1

In a variety of domains, from robotics to finance, Quality-Diversity algorithms have been used to generate collections of both diverse and high-performing solutions. Multi-Objectiv…

cs.NE2024

Exploring the Performance-Reproducibility Trade-off in Quality-Diversity

Manon Flageat, Hannah Janmohamed, Bryan Lim +1

Quality-Diversity (QD) algorithms have exhibited promising results across many domains and applications. However, uncertainty in fitness and behaviour estimations of solutions rema…

cs.NE2024★ 5 cited

Multi-Objective Quality-Diversity for Crystal Structure Prediction

Hannah Janmohamed, Marta Wolinska, Shikha Surana +3

Crystal structures are indispensable across various domains, from batteries to solar cells, and extensive research has been dedicated to predicting their properties based on their…

cs.RO2023★ 1 cited

Quality-Diversity Optimisation on a Physical Robot Through Dynamics-Aware and Reset-Free Learning

Simón C. Smith, Bryan Lim, Hannah Janmohamed +1

Learning algorithms, like Quality-Diversity (QD), can be used to acquire repertoires of diverse robotics skills. This learning is commonly done via computer simulation due to the l…

cs.NE2023★ 2 cited

Improving the Data Efficiency of Multi-Objective Quality-Diversity through Gradient Assistance and Crowding Exploration

Hannah Janmohamed, Thomas Pierrot, Antoine Cully

Quality-Diversity (QD) algorithms have recently gained traction as optimisation methods due to their effectiveness at escaping local optima and capability of generating wide-rangin…