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unthinkable    音标拼音: [ənθ'ɪŋkəbəl]
a. 不能想的,想象不到的,过分的

不能想的,想象不到的,过分的

unthinkable
adj 1: incapable of being conceived or considered [ant:
{thinkable}]

Unthinkable \Unthinkable\
See {thinkable}.

63 Moby Thesaurus words for "unthinkable":
a bit thick, a bit thin, absurd, barred, beyond belief, closed-out,
contrary to reason, doubtable, doubtful, dubious, dubitable,
excluded, extraordinary, hard of belief, hard to believe, hopeless,
illogical, implausible, impossible, improbable, incomprehensible,
inconceivable, incredible, laughable, logically impossible,
ludicrous, mind-blowing, mind-boggling, not deserving belief,
not possible, open to doubt, open to suspicion, oxymoronic,
paradoxical, passing belief, preposterous, problematic, prohibited,
questionable, rare, ridiculous, ruled-out, self-contradictory,
singular, staggering belief, suspect, suspicious, tall, thick,
thin, unacceptable, unbelievable, uncommon, unconvincing,
unearthly, ungodly, unimaginable, unique, unlikely, unordinary,
unusual, unwonted, unworthy of belief


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英文字典中文字典相关资料:


  • Mobile ALOHA
    It augments the ALOHA system with a mobile base, and a whole-body teleoperation interface Using data collected with Mobile ALOHA, we then perform supervised behavior cloning and find that co-training with existing static ALOHA datasets boosts performance on mobile manipulation tasks
  • Mobile ALOHA斯坦福官方网站
    Mobile ALOHA: 使用低成本全身遥操作学习双臂移动操作 人类示范的模仿学习在机器人技术中表现出令人印象深刻的性能。然而，大多数成果专注于桌面操作，缺乏执行一般实用任务所需的移动性和灵巧性。 在这项工作中，我们开发了一个模仿移动操作任务的系统，这些任务是双手的，并且需要全身
  • January 2024 Mobile ALOHA - GitHub Pages
    Mobile ALOHA tasks Core to this system is both (1) , a low-cost whole-body teleoperation system, and (2) the finding that a simple co-training recipe enables data-eficient learning of complex mobile manipu-lation tasks Our teleoperation system is capable of multiple hours of consecutive usage, such as cook-ing a 3-course meal, cleaning a public bathroom, and doing laundry Our imitation
  • January 2024 Mobile ALOHA
    It augments the ALOHA system [104] with a mobile base, and a whole-body teleoperation interface Using data col- lected with Mobile ALOHA, we then perform super- vised behavior cloning and find that co-training with existing static ALOHA datasets boosts performance on mobile manipulation tasks





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