Carlos Florensa

According to our database, Carlos Florensa authored at least 11 papers between 2017 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Which Mutual-Information Representation Learning Objectives are Sufficient for Control?

Kate Rakelly, Abhishek Gupta, Carlos Florensa, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning.

Michelle A. Lee, Carlos Florensa, Jonathan Tremblay, Nathan D. Ratliff, Animesh Garg, Fabio Ramos, Dieter Fox

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Sub-policy Adaptation for Hierarchical Reinforcement Learning.

Alexander C. Li, Carlos Florensa, Ignasi Clavera, Pieter Abbeel

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Self-supervised Learning of Image Embedding for Continuous Control.

Carlos Florensa, Jonas Degrave, Nicolas Heess, Jost Tobias Springenberg, Martin A. Riedmiller

CoRR, 2019

Goal-conditioned Imitation Learning.

Yiming Ding, Carlos Florensa, Pieter Abbeel, Mariano Phielipp

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Adaptive Variance for Changing Sparse-Reward Environments.

Xingyu Lin, Pengsheng Guo, Carlos Florensa, David Held

Proceedings of the International Conference on Robotics and Automation, 2019

2018

Automatic Goal Generation for Reinforcement Learning Agents.

Carlos Florensa, David Held, Xinyang Geng, Pieter Abbeel

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Capacity planning with competitive decision-makers: Trilevel MILP formulation, degeneracy, and solution approaches.

Carlos Florensa, Pablo García-Herreros, Pratik Misra, Erdem Arslan, Sanjay Mehta, Ignacio E. Grossmann

Eur. J. Oper. Res., 2017

Reverse Curriculum Generation for Reinforcement Learning.

Carlos Florensa, David Held, Markus Wulfmeier, Pieter Abbeel

CoRR, 2017

Stochastic Neural Networks for Hierarchical Reinforcement Learning.

Carlos Florensa, Yan Duan, Pieter Abbeel

Proceedings of the 5th International Conference on Learning Representations, 2017

Reverse Curriculum Generation for Reinforcement Learning.

Carlos Florensa, David Held, Markus Wulfmeier, Michael Zhang, Pieter Abbeel

Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017