Luca Weihs

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Aniruddha KembhaviSenior Director of Computer Vision, Allen Institute of Artificial IntelligenceVerified email at allenai.org
Ali FarhadiProfessor, Computer Science and Engineering, University of WashingtonVerified email at cs.uw.edu
Roozbeh MottaghiFAIR, MetaVerified email at cs.stanford.edu
Alvaro HerrastiResearch EngineerVerified email at allenai.org
Jordi SalvadorAllen Institute for AIVerified email at allenai.org
Matt DeitkeAllen Institute for AI; University of Washington, SeattleVerified email at allenai.org
Dustin SchwenkResearch Engineer, Allen Institute for Artificial IntelligenceVerified email at allenai.org
Mathias DrtonProfessor of Mathematical Statistics, Technical University of MunichVerified email at tum.de
Unnat JainCMU and MetaVerified email at illinois.edu
Svetlana LazebnikUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
Alexander SchwingUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
Mark YatskarUniversity of PennsylvaniaVerified email at cis.upenn.edu
Oren EtzioniProfessor, University of WashingtonVerified email at cs.uw.edu
Lucy Lu WangUniversity of Washington; Allen Institute for AI (Ai2)Verified email at uw.edu
Gabriel StanovskyThe Hebrew University of JerusalemVerified email at mail.huji.ac.il
Mohammad RastegariDistinguished AI Scientist at Meta Inc.Verified email at cs.washington.edu
Elina RobevaAssistant Professor, The University of British ColumbiaVerified email at math.ubc.ca
Nicolai MeinshausenProfessor of Statistics, ETH ZurichVerified email at stat.math.ethz.ch
Piotr ZwiernikUniversity of TorontoVerified email at utoronto.ca
Shaowei LinDirector of Research, Topos InstituteVerified email at topos.institute

Luca Weihs

Research Scientist, Allen Institute for Artificial Intelligence

Verified email at allenai.org

reinforcement learning computer vision algebraic statistics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Ai2-thor: An interactive 3d environment for visual ai E Kolve, R Mottaghi, W Han, E VanderBilt, L Weihs, A Herrasti, D Gordon, ... arXiv preprint arXiv:1712.05474, 2019	888	2019
Objaverse: A universe of annotated 3d objects M Deitke, D Schwenk, J Salvador, L Weihs, O Michel, E VanderBilt, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023	512	2023
Robothor: An open simulation-to-real embodied ai platform M Deitke, W Han, A Herrasti, A Kembhavi, E Kolve, R Mottaghi, J Salvador, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020	244	2020
Simple but effective: Clip embeddings for embodied ai A Khandelwal, L Weihs, R Mottaghi, A Kembhavi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022	208	2022
🏘 ProcTHOR: Large-Scale Embodied AI Using Procedural Generation M Deitke, E VanderBilt, A Herrasti, L Weihs, K Ehsani, J Salvador, W Han, ... Advances in Neural Information Processing Systems 35, 5982-5994, 2022	160	2022
Visual room rearrangement L Weihs, M Deitke, A Kembhavi, R Mottaghi Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021	135	2021
Manipulathor: A framework for visual object manipulation K Ehsani, W Han, A Herrasti, E VanderBilt, L Weihs, E Kolve, A Kembhavi, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021	118	2021
Grounded situation recognition S Pratt, M Yatskar, L Weihs, A Farhadi, A Kembhavi Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020	97	2020
Two body problem: Collaborative visual task completion U Jain, L Weihs, E Kolve, M Rastegari, S Lazebnik, A Farhadi, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	85	2019
Gender trends in computer science authorship LL Wang, G Stanovsky, L Weihs, O Etzioni Communications of the ACM 64 (3), 78-84, 2021	65	2021
Symmetric rank covariances: a generalized framework for nonparametric measures of dependence L Weihs, M Drton, N Meinshausen Biometrika 105 (3), 547-562, 2018	62	2018
Allenact: A framework for embodied ai research L Weihs, J Salvador, K Kotar, U Jain, KH Zeng, R Mottaghi, A Kembhavi arXiv preprint arXiv:2008.12760, 2020	59	2020
A cordial sync: Going beyond marginal policies for multi-agent embodied tasks U Jain, L Weihs, E Kolve, A Farhadi, S Lazebnik, A Kembhavi, A Schwing Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020	56	2020
Retrospectives on the embodied ai workshop M Deitke, D Batra, Y Bisk, T Campari, AX Chang, DS Chaplot, C Chen, ... arXiv preprint arXiv:2210.06849, 2022	50	2022
Learning to predict citation-based impact measures L Weihs, O Etzioni 2017 ACM/IEEE joint conference on digital libraries (JCDL), 1-10, 2017	43	2017
Pushing it out of the way: Interactive visual navigation KH Zeng, L Weihs, A Farhadi, R Mottaghi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021	32	2021
Learning Generalizable Visual Representations via Interactive Gameplay L Weihs, A Kembhavi, K Ehsani, SM Pratt, W Han, A Herrasti, E Kolve, ... 9th International Conference on Learning Representations, 2021	30*	2021
Marginal likelihood and model selection for Gaussian latent tree and forest models M Drton, S Lin, L Weihs, P Zwiernik	30	2017
Bridging the imitation gap by adaptive insubordination L Weihs, U Jain, IJ Liu, J Salvador, S Lazebnik, A Kembhavi, A Schwing Advances in Neural Information Processing Systems 34, 19134-19146, 2021	29	2021
Generic identifiability of linear structural equation models by ancestor decomposition M Drton, L Weihs Scandinavian Journal of Statistics 43 (4), 1035-1045, 2016	29	2016

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