| Bdd100k: A diverse driving dataset for heterogeneous multitask learning F Yu, H Chen, X Wang, W Xian, Y Chen, F Liu, V Madhavan, T Darrell Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 1871 | 2020 |
| Bdd100k: A diverse driving video database with scalable annotation tooling F Yu, W Xian, Y Chen, F Liu, M Liao, V Madhavan, T Darrell arXiv preprint arXiv:1805.04687 2 (5), 6, 2018 | 1004 | 2018 |
| Deep neuroevolution: Genetic algorithms are a competitive alternative for training deep neural networks for reinforcement learning FP Such, V Madhavan, E Conti, J Lehman, KO Stanley, J Clune arXiv preprint arXiv:1712.06567, 2017 | 875 | 2017 |
| Improving exploration in evolution strategies for deep reinforcement learning via a population of novelty-seeking agents E Conti, V Madhavan, F Petroski Such, J Lehman, K Stanley, J Clune Advances in neural information processing systems 31, 2018 | 397 | 2018 |
| Best practices for fine-tuning visual classifiers to new domains B Chu, V Madhavan, O Beijbom, J Hoffman, T Darrell Computer Vision–ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8 …, 2016 | 183 | 2016 |
| Scaling map-elites to deep neuroevolution C Colas, V Madhavan, J Huizinga, J Clune Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 67-75, 2020 | 83 | 2020 |
| An atari model zoo for analyzing, visualizing, and comparing deep reinforcement learning agents FP Such, V Madhavan, R Liu, R Wang, PS Castro, Y Li, J Zhi, L Schubert, ... arXiv preprint arXiv:1812.07069, 2018 | 60 | 2018 |
| Decore: Deep compression with reinforcement learning M Alwani, Y Wang, V Madhavan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 28 | 2022 |
| Scalable parameter encoding of artificial neural networks obtained via an evolutionary process FP Such, JM Clune, KO Stanley, E Conti, V Madhavan, JA Lehman US Patent 10,599,975, 2020 | 6 | 2020 |
| Training neural networks using evolution based strategies and novelty search E Conti, V Madhavan, JM Clune, FP Such, JA Lehman, KO Stanley US Patent 11,068,787, 2021 | 2 | 2021 |
| Image Generation from Captions Using Dual-Loss Generative Adversarial Networks V Madhavan, P Cerles, N Desai | 1 | 2016 |
| An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents F Petroski Such, V Madhavan, R Liu, R Wang, PS Castro, Y Li, J Zhi, ... arXiv e-prints, arXiv: 1812.07069, 2018 | | 2018 |
| Examining the Effects of Supervision for Transfer from Synthetic to Real Driving Domains V Madhavan | | |
Jeff CluneCS Assoc. Professor, U. British Columbia; CIFAR AI Chair, Vector; Senior Research Advisor, DeepMindVerified email at ubc.ca
