Vashisht Madhavan
Vashisht Madhavan
Element Inc.
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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
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
Improving exploration in evolution strategies for deep reinforcement learning via a population of novelty-seeking agents
E Conti, V Madhavan, FP Such, J Lehman, K Stanley, J Clune
Advances in neural information processing systems, 5027-5038, 2018
Best practices for fine-tuning visual classifiers to new domains
B Chu, V Madhavan, O Beijbom, J Hoffman, T Darrell
European conference on computer vision, 435-442, 2016
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
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
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning. ArXiv171206567 Cs. 2017
FP Such, V Madhavan, E Conti, J Lehman, KO Stanley, J Clune
URL http://arxiv. org/abs/1712.06567 31, 2017
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
Training neural networks using evolution based strategies and novelty search
E Conti, V Madhavan, JM Clune, FP Such, JA Lehman, KO Stanley
US Patent App. 16/220,533, 2019
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
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, arXiv: 1812.07069, 2018
Examining the Effects of Supervision for Transfer from Synthetic to Real Driving Domains
V Madhavan
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