San Francisco Bay Area, CA

Edoardo Botta

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@EdoardoBotta

MS in ML @ Carnegie Mellon University

RQ-VAE-Recommender. [Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"

823

Gaussian-Mixture-VAE. [Pytorch] Minimal implementation of a Variational Autoencoder (VAE) with Categorical Latent variables inspired from "Categorical Reparameterization with Gumbel-Softmax".

7

rq-kmeans. [Pytorch, Triton] GPU-optimized implementation of kmeans algorithms and RQKmeans vector quantization.

7

RecTokens. [Pytorch] Efficient tokenization for recommendations and generative retrieval. Inspired by STATIC decoding from "Vectorizing the Trie"

7

Vodafone-Hackathon2021. Temporal Convolutional Neural Networks for Complaint Classification

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