collections of examples of gumbel softmax tricks in optimization & deep learning
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Updated
Apr 16, 2024 - Python
collections of examples of gumbel softmax tricks in optimization & deep learning
deep models for small image classification datasets
Code acompanying the paper Developmentally motivated emergence of compositional communication via template transfer
[Pytorch] Minimal implementation of a Variational Autoencoder (VAE) with Categorical Latent variables.
Jittor reimplementation of DiverseSampling (MM22)
The implementation of Gumbel softmax reparametrization trick for discrete VAE
Keras, Tensorflow eager execution implementation of Categorical Variational Autoencoder
Python library for the differentiable hypergeometric distribution
De novo Drug Design via Binary Representations of SMILES for avoiding the Posterior Collapse Problem (BIBM 2021)
Black-box spike and slab variational inference, example with linear models
Implementation of the Gumbel-Sigmoid distribution in PyTorch.
Official project of DiverseSampling (ACMMM2022 Paper)
GAN-Based Text Generation
Code for TACL 2022 paper on Data-to-text Generation with Variational Sequential Planning
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation
TensorFlow-based implementation of "Attend, Infer, Repeat" paper (Eslami et al., 2016, arXiv:1603.08575).
Keras implementation of a Variational Auto Encoder with a Concrete Latent Distribution
An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU) in ICLR 2017.
Codes for "Deep Joint Source-Channel Coding for Wireless Image Transmission with Adaptive Rate Control", ICASSP 2022
TensorFlow GAN implementation using Gumbel Softmax
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