1.7k citations · 3.6k across the 34 of their papers we have counts for
23 papers · 1 filter
Composable Crystals: Controllable Materials Discovery via Concept Learning
Nian Liu, Yuwei Zeng, Ryoji Kubo +7
De novo crystal generation, a central task in materials discovery, aims to generate crystals that are simultaneously valid, stable, unique, and novel. Existing methods mainly rely…
Crys-JEPA: Accelerating Crystal Discovery via Embedding Screening and Generative Refinement
Nian Liu, Nikita Kazeev, Stephen Gregory Dale +8
De novo crystal generation seeks to discover materials that are not merely realistic, but also stable and novel. However, most existing generative models are trained to maximize th…
Feature Collapse
Thomas Laurent, James H. von Brecht, Xavier Bresson
We formalize and study a phenomenon called feature collapse that makes precise the intuitive idea that entities playing a similar role in a learning task receive similar representa…
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning
Xiaoxin He, Xavier Bresson, Thomas Laurent +3
Representation learning on text-attributed graphs (TAGs) has become a critical research problem in recent years. A typical example of a TAG is a paper citation graph, where the tex…
Long-Tailed Learning Requires Feature Learning
Thomas Laurent, James H. von Brecht, Xavier Bresson
We propose a simple data model inspired from natural data such as text or images, and use it to study the importance of learning features in order to achieve good generalization. O…
Combining Reinforcement Learning and Optimal Transport for the Traveling Salesman Problem
Yong Liang Goh, Wee Sun Lee, Xavier Bresson +2
The traveling salesman problem is a fundamental combinatorial optimization problem with strong exact algorithms. However, as problems scale up, these exact algorithms fail to provi…