Timothy Lillicrap
Timothy Lillicrap
collaborator
line weight = collaboration weight
Works in this corpus
| Title | Position | Year | Cited |
|---|---|---|---|
| Mastering the game of Go with deep neural networks and tree search | middle | 2016 | 16,014 |
| Mastering the game of Go without human knowledge | middle | 2017 | 9,313 |
| Continuous control with deep reinforcement learning | first | 2016 | 6,783 |
| Continuous control with deep reinforcement learning | first | 2015 | 5,370 |
| A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play | middle | 2018 | 3,611 |
| Grandmaster level in StarCraft II using multi-agent reinforcement learning | middle | 2019 | 3,508 |
| Asynchronous Methods for Deep Reinforcement Learning | middle | 2016 | 1,689 |
| Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates | middle | 2017 | 1,468 |
| Mastering Atari, Go, chess and shogi by planning with a learned model | middle | 1,374 |
Is this one person?
This record carries a person-claimed ORCID and no signal that it mixes two people.
- supportsAn ORCID is claimed by a person, not inferred, so it is the only identity assertion here that a human made.
- 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.
- supports59% 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.