Unverified50% confidenceFactExact time
At the core of PUN is a neural operator that takes in geometric information and outputs a noise-aware value field.
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Long-term
Relevance
10/21/2026
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Related Claims
UnverifiedPUN (Planning Under Noise) is a neural operator-based planning framework designed to learn a noise-aware value field from noisy Monte Carlo labels, thereby achieving efficient planning in unseen geometric environments.72% similarUnverifiedDeepgram engineers found that audio feature extraction and attention computation are the main performance hotspots of Neuron kernels on speech models.64% similarUnverifiedIncorporating the directional and structural features of traveling waves into decoding models is expected to improve intent recognition accuracy in brain-computer interfaces, especially in high-dimensional decoding tasks such as fine-grained motor commands or continuous speech synthesis.64% similarVerifiedModern neural network VADs such as Silero VAD can distinguish speech from background noise, music, and other audio types at the millisecond level.63% similar
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