2.2k citations · 5.4k across the 32 of their papers we have counts for
5 papers · 1 filter
Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective
Neta Shaul, Itai Gat, Marton Havasi +6
The design space of discrete-space diffusion or flow generative models are significantly less well-understood than their continuous-space counterparts, with many works focusing onl…
FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions
Anuroop Sriram, Benjamin Kurt Miller, Ricky T. Q. Chen +1
Material discovery is a critical area of research with the potential to revolutionize various fields, including carbon capture, renewable energy, and electronics. However, the imme…
Distribution Learning for Molecular Regression
Nima Shoghi, Pooya Shoghi, Anuroop Sriram +1
Using "soft" targets to improve model performance has been shown to be effective in classification settings, but the usage of soft targets for regression is a much less studied top…
FlowMM: Generating Materials with Riemannian Flow Matching
Benjamin Kurt Miller, Ricky T. Q. Chen, Anuroop Sriram +1
Crystalline materials are a fundamental component in next-generation technologies, yet modeling their distribution presents unique computational challenges. Of the plausible arrang…
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text
Nate Gruver, Anuroop Sriram, Andrea Madotto +3
We propose fine-tuning large language models for generation of stable materials. While unorthodox, fine-tuning large language models on text-encoded atomistic data is simple to imp…