default search action
Zachary W. Ulissi
Person information
- affiliation: Carnegie Mellon University, Pittsburgh, PA, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [j14]Xiaoxiao Wang
, Joseph Musielewicz
Generalization of graph-based active learning relaxation strategies across materials. Mach. Learn. Sci. Technol. 5(2): 25018 (2024) - [c5]Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, C. Lawrence Zitnick, Zachary W. Ulissi:
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text. ICLR 2024 - [c4]Nima Shoghi, Adeesh Kolluru, John R. Kitchin, Zachary W. Ulissi, C. Lawrence Zitnick, Brandon M. Wood:
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction. ICLR 2024 - [i12]Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, C. Lawrence Zitnick, Zachary W. Ulissi:
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text. CoRR abs/2402.04379 (2024) - [i11]Christian M. Clausen, Jan Rossmeisl, Zachary W. Ulissi:
Adapting OC20-trained EquiformerV2 Models for High-Entropy Materials. CoRR abs/2403.09811 (2024) - 2023
- [j13]Rohan Yuri Sanspeur
WhereWulff: A Semiautonomous Workflow for Systematic Catalyst Surface Reactivity under Reaction Conditions. J. Chem. Inf. Model. 63(8): 2427-2437 (2023) - [j12]Rajesh K. Raju
Cluster-MLP: An Active Learning Genetic Algorithm Framework for Accelerated Discovery of Global Minimum Configurations of Pure and Alloyed Nanoclusters. J. Chem. Inf. Model. 63(20): 6192-6197 (2023) - [j11]Aaron G. Garrison
Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Data Set. J. Chem. Inf. Model. 63(24): 7642-7654 (2023) - [j10]Muhammed Shuaibi, Yuge Hu
AmpTorch: A Python package for scalable fingerprint-based neural network training on multi-element systems with integrated uncertainty quantification. J. Open Source Softw. 8(87): 5035 (2023) - [i10]Nima Shoghi, Adeesh Kolluru, John R. Kitchin
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction. CoRR abs/2310.16802 (2023) - [i9]Anuroop Sriram, Sihoon Choi, Xiaohan Yu, Logan M. Brabson, Abhishek Das, Zachary W. Ulissi, Matt Uyttendaele, Andrew J. Medford, David S. Sholl:
The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture. CoRR abs/2311.00341 (2023) - 2022
- [j9]Joseph Musielewicz
FINETUNA: fine-tuning accelerated molecular simulations. Mach. Learn. Sci. Technol. 3(3): 3 (2022) - [j8]Yuge Hu
Robust and scalable uncertainty estimation with conformal prediction for machine-learned interatomic potentials. Mach. Learn. Sci. Technol. 3(4): 45028 (2022) - [j7]Johannes Gasteiger, Muhammed Shuaibi, Anuroop Sriram, Stephan Günnemann, Zachary W. Ulissi, C. Lawrence Zitnick, Abhishek Das:
GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets. Trans. Mach. Learn. Res. 2022 (2022) - [c3]Larry Zitnick, Abhishek Das, Adeesh Kolluru, Janice Lan, Muhammed Shuaibi, Anuroop Sriram, Zachary W. Ulissi, Brandon M. Wood:
Spherical Channels for Modeling Atomic Interactions. NeurIPS 2022 - [i8]Johannes Gasteiger, Muhammed Shuaibi, Anuroop Sriram, Stephan Günnemann, Zachary W. Ulissi, C. Lawrence Zitnick, Abhishek Das:
How Do Graph Networks Generalize to Large and Diverse Molecular Systems? CoRR abs/2204.02782 (2022) - [i7]Joseph Musielewicz, Xiaoxiao Wang, Tian Tian, Zachary W. Ulissi:
FINETUNA: Fine-tuning Accelerated Molecular Simulations. CoRR abs/2205.01223 (2022) - [i6]Richard Tran, Janice Lan, Muhammed Shuaibi, Siddharth Goyal, Brandon M. Wood, Abhishek Das, Javier Heras-Domingo
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysis. CoRR abs/2206.08917 (2022) - [i5]C. Lawrence Zitnick, Abhishek Das, Adeesh Kolluru, Janice Lan, Muhammed Shuaibi, Anuroop Sriram
Spherical Channels for Modeling Atomic Interactions. CoRR abs/2206.14331 (2022) - [i4]Janice Lan, Aini Palizhati, Muhammed Shuaibi, Brandon M. Wood, Brook Wander, Abhishek Das, Matt Uyttendaele, C. Lawrence Zitnick, Zachary W. Ulissi:
AdsorbML: Accelerating Adsorption Energy Calculations with Machine Learning. CoRR abs/2211.16486 (2022) - 2021
- [j6]Muhammed Shuaibi, Saurabh Sivakumar
Enabling robust offline active learning for machine learning potentials using simple physics-based priors. Mach. Learn. Sci. Technol. 2(2): 25007 (2021) - [j5]Junwoong Yoon, Zhonglin Cao
Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy. Mach. Learn. Sci. Technol. 2(4): 45018 (2021) - [c2]Abhishek Das, Muhammed Shuaibi, Aini Palizhati, Siddharth Goyal, Aditya Grover, Adeesh Kolluru, Janice Lan, Ammar Rizvi, Anuroop Sriram, Brandon M. Wood, Devi Parikh, Zachary W. Ulissi, C. Lawrence Zitnick, Guolin Ke, Shuxin Zheng, Yu Shi, Di He, Tie-Yan Liu, Chengxuan Ying, Jiacheng You, Yihan He, Rostislav Grigoriev, Ruslan Lukin, Adel Yarullin, Max Faleev:
The Open Catalyst Challenge 2021: Competition Report. NeurIPS (Competition and Demos) 2021: 29-40 - [i3]Muhammed Shuaibi, Adeesh Kolluru, Abhishek Das, Aditya Grover, Anuroop Sriram, Zachary W. Ulissi, C. Lawrence Zitnick:
Rotation Invariant Graph Neural Networks using Spin Convolutions. CoRR abs/2106.09575 (2021) - 2020
- [j4]Kevin Tran
Methods for comparing uncertainty quantifications for material property predictions. Mach. Learn. Sci. Technol. 1(2): 25006 (2020) - [i2]C. Lawrence Zitnick, Lowik Chanussot, Abhishek Das, Siddharth Goyal, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Thibaut Lavril, Aini Palizhati, Morgane Riviere, Muhammed Shuaibi, Anuroop Sriram, Kevin Tran, Brandon M. Wood, Junwoong Yoon, Devi Parikh, Zachary W. Ulissi:
An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage. CoRR abs/2010.09435 (2020) - [i1]Lowik Chanussot, Abhishek Das, Siddharth Goyal, Thibaut Lavril, Muhammed Shuaibi, Morgane Riviere, Kevin Tran, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Aini Palizhati, Anuroop Sriram, Brandon M. Wood, Junwoong Yoon, Devi Parikh, C. Lawrence Zitnick, Zachary W. Ulissi:
The Open Catalyst 2020 (OC20) Dataset and Community Challenges. CoRR abs/2010.09990 (2020)
2010 – 2019
- 2019
- [j3]Aini Palizhati, Wen Zhong, Kevin Tran
Toward Predicting Intermetallics Surface Properties with High-Throughput DFT and Convolutional Neural Networks. J. Chem. Inf. Model. 59(11): 4742-4749 (2019) - 2018
- [j2]Kevin Tran
Dynamic Workflows for Routine Materials Discovery in Surface Science. J. Chem. Inf. Model. 58(12): 2392-2400 (2018) - 2013
- [j1]Zachary W. Ulissi, Michael S. Strano, Richard D. Braatz:
Control of nano and microchemical systems. Comput. Chem. Eng. 51: 149-156 (2013) - 2012
- [c1]Zachary W. Ulissi, Mark C. Molaro, Michael S. Strano, Richard D. Braatz:
Systems nanotechnology: Identification, estimation, and control of nanoscale systems. ACC 2012: 1-7
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 21:18 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: