| Large-scale visual active learning with deep probabilistic ensembles K Chitta, JM Alvarez, A Lesnikowski arXiv preprint arXiv:1811.03575, 2018 | 8 | 2018 |
| Training Data Distribution Search with Ensemble Active Learning K Chitta, JM Alvarez, E Haussmann, C Farabet arXiv preprint arXiv:1905.12737, 2019 | 5* | 2019 |
| Adaptive semantic segmentation with a strategic curriculum of proxy labels K Chitta, J Feng, M Hebert arXiv preprint arXiv:1811.03542, 2018 | 5 | 2018 |
| Learning Situational Driving E Ohn-Bar, A Prakash, A Behl, K Chitta, A Geiger Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 2 | 2020 |
| Learning Sampling Policies for Domain Adaptation Y Patel, K Chitta, B Jasani arXiv preprint arXiv:1805.07641, 2018 | 2 | 2018 |
| A reduced region of interest based approach for facial expression recognition from static images K Chitta, NN Sajjan 2016 IEEE Region 10 Conference (TENCON), 2806-2809, 2016 | 2 | 2016 |
| Scalable Active Learning for Object Detection E Haussmann, M Fenzi, K Chitta, J Ivanecky, H Xu, D Roy, A Mittel, ... arXiv preprint arXiv:2004.04699, 2020 | 1 | 2020 |
| Exploring Data Aggregation in Policy Learning for Vision-based Urban Autonomous Driving A Prakash, A Behl, E Ohn-Bar, K Chitta, A Geiger Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 1 | 2020 |
| Targeted Kernel Networks: Faster Convolutions with Attentive Regularization K Chitta Proceedings of the European Conference on Computer Vision (ECCV), 0-0, 2018 | 1 | 2018 |
| Unmasking the Inductive Biases of Unsupervised Object Representations for Video Sequences MA Weis, K Chitta, Y Sharma, W Brendel, M Bethge, A Geiger, AS Ecker arXiv preprint arXiv:2006.07034, 2020 | | 2020 |
| Label Efficient Visual Abstractions for Autonomous Driving A Behl, K Chitta, A Prakash, E Ohn-Bar, A Geiger arXiv preprint arXiv:2005.10091, 2020 | | 2020 |
| Quadtree Generating Networks: Efficient Hierarchical Scene Parsing with Sparse Convolutions K Chitta, JM Alvarez, M Hebert The IEEE Winter Conference on Applications of Computer Vision, 2020 | | 2020 |
| Deep Probabilistic Ensembles: Approximate Variational Inference through KL Regularization K Chitta, JM Alvarez, A Lesnikowski NeurIPS Workshop on Bayesian Deep Learning, 2018 | | 2018 |
| Supplementary Material for Learning Situational Driving E Ohn-Bar, A Prakash, A Behl, K Chitta, A Geiger | | |
| Supplementary Material for Exploring Data Aggregation in Policy Learning for Vision-based Urban Autonomous Driving A Prakash, A Behl, E Ohn-Bar, K Chitta, A Geiger | | |
Jose M. AlvarezNVIDIAVerified email at nvidia.com
