C. Lawrence Zitnick

Computer Science · Physical Sciences

63h-index78.7kcitations152works19.22yr avg
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Research Topics

Advanced Image and Video Retrieval Techniques(48), Multimodal Machine Learning Applications(38), Advanced Vision and Imaging(29), Machine Learning in Materials Science(20), Domain Adaptation and Few-Shot Learning(17)

Publications152 total

The Open Catalyst 2025 (OC25) Dataset and Models for Solid-Liquid Interfaces
ArXiv.org·2025· 3 citedOpen Access
Open Molecular Crystals 2025 (OMC25) Dataset and Models
ArXiv.org·2025· 1 citedOpen Access
FastCSP: Accelerated Molecular Crystal Structure Prediction with Universal Model for Atoms
arXiv (Cornell University)·2025· 1 citedOpen Access
UMA: A Family of Universal Models for Atoms
ArXiv.org·2025· 14 citedOpen Access
CatTSunami: Accelerating Transition State Energy Calculations with Pretrained Graph Neural Networks
ACS Catalysis·2025· 24 cited
Learning Smooth and Expressive Interatomic Potentials for Physical Property Prediction
ArXiv.org·2025· 20 citedOpen Access
Open Catalyst Experiments 2024 (OCx24): Bridging Experiments and Computational Models
arXiv (Cornell University)·2024· 15 citedOpen Access
Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models
arXiv (Cornell University)·2024· 74 citedOpen Access
CatTSunami: Accelerating Transition State Energy Calculations with Pre-trained Graph Neural Networks
arXiv (Cornell University)·2024· 7 citedOpen Access
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text
arXiv (Cornell University)·2024· 33 citedOpen Access
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction
arXiv (Cornell University)·2023· 21 citedOpen Access
AdsorbML: a leap in efficiency for adsorption energy calculations using generalizable machine learning potentials
npj Computational Materials·2023· 82 citedOpen Access
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts
ACS Catalysis·2023· 253 cited
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs
arXiv (Cornell University)·2023· 26 citedOpen Access
Deep Learning Reconstruction Enables Prospectively Accelerated Clinical Knee MRI
Radiology·2023· 106 citedOpen Access
Open Challenges in Developing Generalizable Large-Scale Machine-Learning Models for Catalyst Discovery
ACS Catalysis·2022· 60 cited
Spherical Channels for Modeling Atomic Interactions
arXiv (Cornell University)·2022· 35 citedOpen Access
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts
arXiv (Cornell University)·2022· 13 citedOpen Access
Open Challenges in Developing Generalizable Large Scale Machine Learning Models for Catalyst Discovery
arXiv (Cornell University)·2022· 2 citedOpen Access
Transfer learning using attentions across atomic systems with graph neural networks (TAAG)
The Journal of Chemical Physics·2022· 31 cited
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Frequent Co-authors

Devi Parikh(9), Piotr Dollár(8), Sing Bing Kang(8), Richard Szeliski(8), Margaret Mitchell(7), Anuroop Sriram(7), Aishwarya Agrawal(5), Dhruv Batra(5), Ross Girshick(5), Jure Žbontar(5), Florian Knöll(5), Matthew J. Muckley(5), Michael P. Recht(5), Daniel K. Sodickson(5), Siddharth Goyal(4), Aaron Defazio(4), Michael Rabbat(4), Nafissa Yakubova(4), Neel Joshi(4), Brian Curless(4)