collections of examples of gumbel softmax tricks in optimization & deep learning

deep models for small image classification datasets

Python library for the differentiable hypergeometric distribution

Jittor reimplementation of DiverseSampling (MM22)

The implementation of Gumbel softmax reparametrization trick for discrete VAE

Official project of DiverseSampling (ACMMM2022 Paper)

[BMM 24-25] Implementation of different relaxation methods

Implementation of the Gumbel-Sigmoid distribution in PyTorch.

Black-box spike and slab variational inference, example with linear models

Code for TACL 2022 paper on Data-to-text Generation with Variational Sequential Planning

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

De novo Drug Design via Binary Representations of SMILES for avoiding the Posterior Collapse Problem (BIBM 2021)

Keras, Tensorflow eager execution implementation of Categorical Variational Autoencoder

Code acompanying the paper Developmentally motivated emergence of compositional communication via template transfer

GAN-Based Text Generation

TensorFlow-based implementation of "Attend, Infer, Repeat" paper (Eslami et al., 2016, arXiv:1603.08575).

A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation

Implementation of NeurIPS 19 paper: Paraphrase Generation with Latent Bag of Words

Keras implementation of a Variational Auto Encoder with a Concrete Latent Distribution

Source code for the NAACL 2019 paper "SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression"