Differentiable Annealed Importance Sampling (DAIS)

This repository contains the code to reproduce the DAIS results from the paper Differentiable Annealed Importance Sampling and the Perils of Gradient Noise.

Bayesian Linear Regression

Please first install JAX (https://github.com/google/jax), then reproduce our results by running the following:

python blr/dais.py --gamma 0.0
python blr/dais.py --gamma 0.9
python blr.dais.py --bsize 100

Variational Autoencoder

Please first install PyTorch (https://pytorch.org/).

For training, one example command for DAIS with $K = 10$ and $S = 5$ (to adapt annealing scheme, add --adapt_beta):

python vae/mnist_train.py --lf_step 10 --n_particles 5 --lf_lrate 0.08

After training, you can find the saved checkpoint and evaluate it (e.g., using AIS):

python vae/mnist_eval.py --ais --n_particles 10 --lf_step 10000 --lf_lrate 0.05 --resume xxx

Also, you can reproduce the evaulation results of AIS/HAIS/DAIS by runing vae/mnist_eval_scaling.py:

python vae/mnist_eval_scaling.py --linear_beta --lf_lrate 0.08 --n_particles 10 --resume xxx

Citation

To cite this work, please use

@inproceedings{
	zhang2021differentiable,
	title={Differentiable Annealed Importance Sampling and the Perils of Gradient Noise},
	author={Guodong Zhang and Kyle Hsu and Jianing Li and Chelsea Finn and Roger Baker Grosse},
	booktitle={Thirty-Fifth Conference on Neural Information Processing Systems},
	year={2021},
	url={https://openreview.net/forum?id=6rqjgrL7Lq}
}

Differentiable Annealed Importance Sampling (DAIS)

Related tags

Overview

Differentiable Annealed Importance Sampling (DAIS)

Bayesian Linear Regression

Variational Autoencoder

Citation

Owner

Guodong Zhang

VoxHRNet - Whole Brain Segmentation with Full Volume Neural Network

Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

This is the pytorch implementation for the paper: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation, which is accepted to ICCV2021.

Source code for "Taming Visually Guided Sound Generation" (Oral at the BMVC 2021)

Clinica is a software platform for clinical research studies involving patients with neurological and psychiatric diseases and the acquisition of multimodal data

A ssl analyzer which could analyzer target domain's certificate.

Hydra Lightning Template for Structured Configs

PyTorch original implementation of Cross-lingual Language Model Pretraining.

Survival analysis (SA) is a well-known statistical technique for the study of temporal events.

AquaTimer - Programmable Timer for Aquariums based on ATtiny414/814/1614

Face Mask Detection System built with OpenCV, TensorFlow using Computer Vision concepts

Official Implementation of SWAGAN: A Style-based Wavelet-driven Generative Model

I explore rock vs. mine prediction using a SONAR dataset

Simulation-based inference for the Galactic Center Excess

A PyTorch library for Vision Transformers

Content shared at DS-OX Meetup

The official PyTorch code for 'DER: Dynamically Expandable Representation for Class Incremental Learning' accepted by CVPR2021

PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"

Bayesian inference for Permuton-induced Chinese Restaurant Process (NeurIPS2021).

Official DGL implementation of "Rethinking High-order Graph Convolutional Networks"