max-ilse

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

google-images-download

Python Script to download hundreds of images from 'Google Images'. It is a ready-to-run code!

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

torchdiffeq

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

pytorch-OpCounter

Count the MACs / FLOPs of your PyTorch model.

DomainBed

DomainBed is a suite to test domain generalization algorithms

former

Simple transformer implementation from scratch in pytorch.

robustness

Corruption and Perturbation Robustness (ICLR 2019)

dsprites-dataset

Dataset to assess the disentanglement properties of unsupervised learning methods

pytorch-SRResNet

pytorch implementation for Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network arXiv:1609.04802

InvariantRiskMinimization

PyTorch code to run synthetic experiments.

torchvggish

Pytorch port of Google Research's VGGish model used for extracting audio features.

PyTorch-SRGAN

A modern PyTorch implementation of SRGAN

deepscm

Repository for Deep Structural Causal Models for Tractable Counterfactual Inference

residual-flows

code for "Residual Flows for Invertible Generative Modeling".

nsf

Code for Neural Spline Flows paper

JigenDG

Repository for the CVPR19 oral paper "Domain Generalization by Solving Jigsaw Puzzles"

LSQuantization

The PyTorch implementation of Learned Step size Quantization (LSQ) in ICLR2020 (unofficial)

DIVA

Implementation of 'DIVA: Domain Invariant Variational Autoencoders'

invariant-risk-minimization

Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893

Morpho-MNIST

Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning (http://jmlr.org/papers/v20/19-033.html)

carefl

Code for "Causal autoregressive flows" - AISTATS, 2021

inv-rep

Code for Invariant Rep. Without Adversaries (NIPS 2018)

credence-to-causal-estimation

A framework for generating complex and realistic datasets for use in evaluating causal inference methods.

SNIP-it

This repository is the official implementation of the paper Pruning via Iterative Ranking of Sensitivity Statistics and implements novel pruning / compression algorithms for deep learning / neural networks. Amongst others it implements structured pruning before training, its actual parameter shrinking and unstructured before/during training.

LRS_NF

[AISTATS2020] The official repository of "Invertible Generative Modling using Linear Rational Splines (LRS)".

Unified-Adversarial-Invariance

invariance-tutorial

A tutorial on learned non-adversarial invariance in neural networks

core

TensorFlow implementation of 'Core', proposed in "Conditional Variance Penalties and Domain Shift Robustness".

Multi-View-Information-Bottleneck