neural networks as stat mech systems
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Neural Networks as Stat Mech Systems Based on arXiv:1710.06570 - PowerPoint PPT Presentation

Neural Networks as Stat Mech Systems Based on arXiv:1710.06570 [stat.ML], A Correspondence Between Random Neural Networks and Statistical Field Theory Yoni Kahn, KICP/UIUC hep-ai 1/8/19 <latexit


  1. Neural Networks 
 as 
 Stat Mech Systems Based on arXiv:1710.06570 [stat.ML], “A Correspondence Between Random Neural Networks and Statistical Field Theory” Yoni Kahn, KICP/UIUC 
 hep-ai 1/8/19

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sha1_base64="ah+KiWCtDx9PIzoqxt0DK9fgMP0=">AB73icdVDLSsNAFJ3UV62vqks3g0WoUEoSQ1t3RTeupEJf2IYymU7aoZNJnJkIJfQn3LhQxK2/486/cdJWUNEDFw7n3Mu93gRo1KZ5oeRWVldW9/Ibua2tnd29/L7B20ZxgKTFg5ZKLoekoRTlqKka6kSAo8BjpeJPL1O/cEyFpyJtqGhE3QCNOfYqR0lL3tnhdapeap4N8wSyf1yq2U4Fm2TSrlm2lxK46Zw60tJKiAJZoDPLv/WGI4BwhRmSsmeZkXITJBTFjMxy/ViSCOEJGpGephwFRLrJ/N4ZPNHKEPqh0MUVnKvfJxIUSDkNPN0ZIDWv71U/MvrxcqvuQnlUawIx4tFfsygCmH6PBxSQbBiU0QFlTfCvEYCYSVjinQ/j6FP5P2nbZ0vzGKdQvlnFkwRE4BkVgSqogyvQAC2AQMP4Ak8G3fGo/FivC5aM8Zy5hD8gPH2CZrCjwc=</latexit> <latexit sha1_base64="ah+KiWCtDx9PIzoqxt0DK9fgMP0=">AB73icdVDLSsNAFJ3UV62vqks3g0WoUEoSQ1t3RTeupEJf2IYymU7aoZNJnJkIJfQn3LhQxK2/486/cdJWUNEDFw7n3Mu93gRo1KZ5oeRWVldW9/Ibua2tnd29/L7B20ZxgKTFg5ZKLoekoRTlqKka6kSAo8BjpeJPL1O/cEyFpyJtqGhE3QCNOfYqR0lL3tnhdapeap4N8wSyf1yq2U4Fm2TSrlm2lxK46Zw60tJKiAJZoDPLv/WGI4BwhRmSsmeZkXITJBTFjMxy/ViSCOEJGpGephwFRLrJ/N4ZPNHKEPqh0MUVnKvfJxIUSDkNPN0ZIDWv71U/MvrxcqvuQnlUawIx4tFfsygCmH6PBxSQbBiU0QFlTfCvEYCYSVjinQ/j6FP5P2nbZ0vzGKdQvlnFkwRE4BkVgSqogyvQAC2AQMP4Ak8G3fGo/FivC5aM8Zy5hD8gPH2CZrCjwc=</latexit> Motivation Neural networks have extremely large numbers 
 of parameters. On the surface, that makes them hard to understand analytically. But physics provides examples where systems simplify 
 in the limit of large numbers of constituents: 
 thermodynamics/stat mech. N ∼ 10 23 Z ( N, V, T ) Ψ ( x 1 , x 2 , . . . , x N )

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