2026-10-14 · America/Los_Angeles · 社区动态 · #11

Event2Vec: additive event embeddings where a linear score on a history decomposes exactly into per-event terms [P]

I've been working on Event2Vec, a small library for learning embeddings of discrete event sequences (purchases, logs, clinical codes, etc.) with a deliberately simple structure: a history is the running sum of its event vectors. h_t = h_{t-1} + e_{x_t} (norm-clipped) p(x_{t+1} | h_t) = softmax(W h_t + b) Training is self-supervised next-event prediction, plus a reconstruction term that asks h_t - h_{t-1} to recover e_{x_t} . No labels needed (details why the machinery works are in NeurReps@NeuralIPS Workshop paper, it is a bunch of losses that attempts the reconstruction and obey the…

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