BSA-TNP is a new neural process model with KRBlocks and biased scan attention that claims to match top accuracy while scaling inference to over 1M points in under a minute on a single GPU and supporting translation invariance.
JAX: composable transformations of Python+NumPy programs, 2018
3 Pith papers cite this work. Polarity classification is still indexing.
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TAE combines Tikhonov regularization with autoencoders and a data randomization strategy to learn forward and inverse surrogates from one sample, with linear error bounds and tests on heat inversion and Navier-Stokes reconstruction.
Model-free RNN agents in Overcooked-AI spontaneously develop structured internal models of partner abilities when they can allocate tasks, enabling adaptation to novel collaborators.
citing papers explorer
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Scalable Spatiotemporal Inference with Biased Scan Attention Transformer Neural Processes
BSA-TNP is a new neural process model with KRBlocks and biased scan attention that claims to match top accuracy while scaling inference to over 1M points in under a minute on a single GPU and supporting translation invariance.
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TAEN: A Model-Constrained Tikhonov Autoencoder Network for Forward and Inverse Problems
TAE combines Tikhonov regularization with autoencoders and a data randomization strategy to learn forward and inverse surrogates from one sample, with linear error bounds and tests on heat inversion and Navier-Stokes reconstruction.
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Partner Modelling Emerges in Recurrent Agents (But Only When It Matters)
Model-free RNN agents in Overcooked-AI spontaneously develop structured internal models of partner abilities when they can allocate tasks, enabling adaptation to novel collaborators.