CLeAR

Software

On this page, you’ll find links to software, code repositories and datasets that the CLeAR lab has produced.


IROS2020TactileSGNet

This repository contains code for the IROS 2020 paper “TactileSGNet: A Spiking Graph Neural Network for Event-based Tactile Object Recognition”. In this paper, we propose a novel spiking graph neural network for event-based tactile object recognition. [Check our Github Page]


ICLR2021DGflow

This repository contains code for reproducing the experiments presented in the ICLR 2021 paper Refining Deep Generative Models via Discriminator Gradient Flow. In this paper, we propose DGflow, a technique to improve samples from deep generative models using the gradient flow of entropy-regularized f-divergences between the generated and real data distributions. [Check our Github Page]


CVPR2020OCFGAN

This repository contains code for the CVPR 2020 paper: A Characteristic Function Approach to Deep Implicit Generative Modeling. In this paper, we propose a method of training a Generative Adversarial Network (GAN) by minimizing the expected distance between empirical characteristic functions of the real and generated data distributions.[Check our Github Page]


AAAI2019CHyVAE

This repository contains code for the AAAI 2019 paper: Hyperprior Induced Unsupervised Disentanglement of Latent Representations. In this paper, we show how a simple hierarchical Bayesian VAE leads to controllable latent representations.[Check our Github Page]