@article{TEXTUAL,
      recid = {14692},
      author = {Falk, Martin J. and Strupp, Adam T. and Scellier, Benjamin  and Murugan, Arvind},
      title = {Temporal Contrastive Learning through implicit  non-equilibrium memory},
      journal = {Nature Communications},
      address = {2025-03-04},
      number = {TEXTUAL},
      abstract = {The backpropagation method has enabled transformative uses  of neural networks. Alternatively, for energy-based models,  local learning methods involving only nearby neurons offer  benefits in terms of decentralized training, and allow for  the possibility of learning in computationally-constrained  substrates. One class of local learning methods contrasts  the desired, clamped behavior with spontaneous, free  behavior. However, directly contrasting free and clamped  behaviors requires explicit memory. Here, we introduce  ‘Temporal Contrastive Learning’, an approach that uses  integral feedback in each learning degree of freedom to  provide a simple form of implicit non-equilibrium memory.  During training, free and clamped behaviors are shown in a  sawtooth-like protocol over time. When combined with  integral feedback dynamics, these alternating temporal  protocols generate an implicit memory necessary for  comparing free and clamped behaviors, broadening the range  of physical and biological systems capable of contrastive  learning. Finally, we show that non-equilibrium dissipation  improves learning quality and determine a Landauer-like  energy cost of contrastive learning through physical  dynamics.},
      url = {http://knowledge.uchicago.edu/record/14692},
}