Pieter Abbeel
Pieter Abbeel
collaborator
line weight = collaboration weight
Works in this corpus
| Title | Position | Year | Cited |
|---|---|---|---|
| Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks | middle | 2017 | 5,794 |
| Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor | middle | 2018 | 3,500 |
| Trust Region Policy Optimization | last | 2015 | 3,129 |
| Apprenticeship learning via inverse reinforcement learning | first | 2004 | 2,895 |
| Domain randomization for transferring deep neural networks from simulation to the real world | last | 2017 | 2,890 |
| Soft Actor-Critic Algorithms and Applications | middle | 2018 | 1,994 |
| High-Dimensional Continuous Control Using Generalized Advantage Estimation | last | 2015 | 1,746 |
| End-to-end training of deep visuomotor policies | last | 2016 | 1,706 |
| End-to-End Training of Deep Visuomotor Policies | last | 2015 | 1,400 |
Is this one person?
This record is probably one person, but at least one signal is weak. Check the evidence below before relying on the totals.
- neutralNo ORCID on this record, so its identity rests on inference alone.
- supports2 distinct name form(s) across this row's works, counting a spelled-out given name and its initial as one form.
- supportsAt most 3 distinct institution(s) inside any five-year window, which is a normal career.
- supports67% of this row's works sit in its single largest field.
- neutralConfidence is judged on the 9 work(s) this corpus holds, not on the author's whole output. A single-work row carries little evidence either way.