A computational phase transition for learning-to-sample from Ising models
Why it matters
Simons Institute describes June Vuong studying generative learning through learning-to-sample from Ising models. The talk contrasts efficient algorithms below a spectral threshold with cryptographic hardness beyond it, and discusses a…
Simons Institute's description presents Max Simchowitz questioning why diffusion and flow policies improve robotics performance. The abstract argues that iterative computation and training noise may explain gains better than fitting multimodal action distributions. It is a research claim worth…
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