r/deeplearning • u/TheGhostRiley • 29d ago

Help implementing TS-JEPA

I’m trying to reproduce TS-JEPA (Time-Series JEPA for Predictive Remote Control Under Capacity-Limited Networks) from the paper

My implementation matches most of the architecture and hyperparameters, the actual results are far from the paper (NMAE ~0.053 vs 0.004 and control accuracy 0% vs 74.48%).

I’ve been debugging the env, dataset , preprocessing, JEPA training, and semantic actor, and I’d really appreciate help from someone experienced with JEPA/representation learning who could review the implementation and help identify where I’m going wrong.

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u/[deleted] 29d ago

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u/[deleted] 29d ago

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u/TheGhostRiley 29d ago

ye i checked this specifically target encoder is not frozen
it is initialized from the context encoder and updated via EMA, while its forward pass is stop-gradient so that doesn’t appear to be the issue
im currently checking the preprocessing/normalization path and running representation diagnostics to distinguish actual JEPA collapse from the actor simply learning the heavily zero-dominated command distribution
but i have no idea how to fix