The official repository for our paper "The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers". We significantly improve the systematic generalization of transformer models on a variety of datasets using simple tricks and careful considerations.

Simple (but often Strong) Baselines for POMDPs in PyTorch - ICML 2022

Implementation of the paper Recurrent Independent Mechanisms (https://arxiv.org/pdf/1909.10893.pdf)

Winning Solution of the NeurIPS 2020 Competition on Predicting Generalization in Deep Learning

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Awesome Domain Adaptation Python Toolbox

Improving generalization by controlling label-noise information in neural network weights.

Awesome list for Neural Network Optimization methods.

Source code and dataset for the CCKS201 paper "On Robustness and Bias Analysis of BERT-based Relation Extraction"

Code for 3D Reconstruction of Novel Object Shapes from Single Images paper

[CVPR 2021] SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration

The official repository for our paper "Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks". We develop a method for analyzing emerging functional modularity in neural networks based on differentiable weight masks and use it to point out important issues in current-day neural networks.

generalize counter-examples of property-based testing

This repository contains code to replicate the experiments given in NeurIPS 2019 paper "One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers"

Computing various norms/measures on over-parametrized neural networks