activity
20192026
most citedMatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures

108 citations · 287 across the 10 of their papers we have counts for

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Showing 2026Show all

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quant-ph2026

Designing Quantum Error Correcting Codes to fit decoders via Reinforcement Learning

Omer S. Sella, Robert Pinsler, Thomas Heinis

We present a reinforcement learning (RL) approach to the co-design of stabilizer sets of Quantum Error Correcting Codes (QECCs) and decoders. We show how to produce a generative mo…

cond-mat.mtrl-sci2026

MatterSim-MT: A multi-task foundation model for in silico materials characterization

Han Yang, Xixian Liu, Chenxi Hu +25

Accurate property characterization is a major bottleneck in materials design. While first-principles methods and task-specific machine-learning models have driven important progres…