Seuraa
Luca Weihs
Luca Weihs
Research Scientist, Allen Institute for Artificial Intelligence
Vahvistettu sähköpostiosoite verkkotunnuksessa allenai.org
Nimike
Viittaukset
Viittaukset
Vuosi
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
4032019
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
792020
Symmetric rank covariances: a generalized framework for nonparametric measures of dependence
L Weihs, M Drton, N Meinshausen
Biometrika 105 (3), 547-562, 2018
402018
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
352019
Learning to predict citation-based impact measures
L Weihs, O Etzioni
2017 ACM/IEEE joint conference on digital libraries (JCDL), 1-10, 2017
302017
Gender trends in computer science authorship
LL Wang, G Stanovsky, L Weihs, O Etzioni
Communications of the ACM 64 (3), 78-84, 2021
292021
Visual room rearrangement
L Weihs, M Deitke, A Kembhavi, R Mottaghi
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021
272021
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
262021
Grounded situation recognition
S Pratt, M Yatskar, L Weihs, A Farhadi, A Kembhavi
European Conference on Computer Vision, 314-332, 2020
252020
Generic identifiability of linear structural equation models by ancestor decomposition
M Drton, L Weihs
Scandinavian Journal of Statistics 43 (4), 1035-1045, 2016
252016
Efficient computation of the Bergsma–Dassios sign covariance
L Weihs, M Drton, D Leung
Computational Statistics 31 (1), 315-328, 2016
232016
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
European Conference on Computer Vision, 471-490, 2020
212020
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
202020
Large-sample theory for the Bergsma-Dassios sign covariance
P Nandy, L Weihs, M Drton
Electronic Journal of Statistics 10 (2), 2287-2311, 2016
182016
Marginal likelihood and model selection for Gaussian latent tree and forest models
M Drton, S Lin, L Weihs, P Zwiernik
Bernoulli 23 (2), 1202-1232, 2017
162017
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
13*2021
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
102022
Nested covariance determinants and restricted trek separation in Gaussian graphical models
M Drton, E Robeva, L Weihs
Bernoulli 26 (4), 2503-2540, 2020
92020
Visual reaction: Learning to play catch with your drone
KH Zeng, R Mottaghi, L Weihs, A Farhadi
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
92020
Gridtopix: Training embodied agents with minimal supervision
U Jain, IJ Liu, S Lazebnik, A Kembhavi, L Weihs, AG Schwing
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
82021
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Artikkelit 1–20