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Everyone can now train high-dimensional muscle agents with RL, as we just released our code! Come join me at the #MyoChallenge workshop tomorrow at 10:00 in room 354 at #NeurIPS2023 to see my poster. Code is here!
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rlfromlux's profile picture

Everyone can now train high-dimensional muscle agents with RL, as we just released our code! Come join me at the #MyoChallenge workshop tomorrow at 10:00 in room 354 at #NeurIPS2023 to see my poster. Code is here!

Pierre Schumacher

159,528 просмотров • 2 лет назад

Watch Fraser Mince present “The Grand Illusion: The Myth of Software Portability and Implications for ML Progress” at #NeurIPS2023 Work with Dzung Dinh Jonas Neil Thompson Sara Hooker at Cohere For AI and MIT IDE Read more:
1:56
cohere's profile picture

Watch Fraser Mince present “The Grand Illusion: The Myth of Software Portability and Implications for ML Progress” at #NeurIPS2023 Work with Dzung Dinh Jonas Neil Thompson Sara Hooker at Cohere For AI and MIT IDE Read more:

Cohere

38,093 просмотров • 2 лет назад

Awesome poster presentation by Niklas Muennighoff for the paper "Scaling Data-Constrained Language Models" at #NeurIPS2023 Kudos Sasha Rush Boaz Barak Teven Le Scao Ola Piktus Nouamane Tazi Sampo Pyysalo Thomas Wolf @colinraffel
1:59
JayAlammar's profile picture

Awesome poster presentation by Niklas Muennighoff for the paper "Scaling Data-Constrained Language Models" at #NeurIPS2023 Kudos Sasha Rush Boaz Barak Teven Le Scao Ola Piktus Nouamane Tazi Sampo Pyysalo Thomas Wolf @colinraffel

Jay Alammar

29,377 просмотров • 2 лет назад

I caught up with Amanda Bertsch at #NeurIPS2023, who was presenting Unlimiformer, a retrieval-augmentation method for encoder-decoder models allowing unlimited length inputs. Paper: Unlimiformer: Long-Range Transformers with Unlimited Length Input Work with Uri Alon Graham Neubig, and Matt Gormley More #NeurIPS2023 coverage to come (Follow Cohere to not miss any of it).
1:21
JayAlammar's profile picture

I caught up with Amanda Bertsch at #NeurIPS2023, who was presenting Unlimiformer, a retrieval-augmentation method for encoder-decoder models allowing unlimited length inputs. Paper: Unlimiformer: Long-Range Transformers with Unlimited Length Input Work with Uri Alon Graham Neubig, and Matt Gormley More #NeurIPS2023 coverage to come (Follow Cohere to not miss any of it).

Jay Alammar

25,862 просмотров • 2 лет назад

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