Popular GitHub Repositories for Neurips 2020

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training

Learn fast, scalable, and calibrated measures of uncertainty using neural networks!

Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)

Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"

Codes for NeurIPS 2020 paper "Adversarial Weight Perturbation Helps Robust Generalization"

Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with an oral spotlight!) at ML4H Workshop, NeurIPS 2020.

[NeurIPS 2020] Official PyTorch Implementation of "Residual Force Control for Agile Human Behavior Imitation and Extended Motion Synthesis". NeurIPS 2020.

Meta-Learning through Hebbian Plasticity in Random Networks: https://arxiv.org/abs/2007.02686

Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)

(NeurIPS 2020 oral) Code for "Deep Transformation-Invariant Clustering" paper

Adversarial Distributional Training (NeurIPS 2020)

Hybrid Models for Learning to Branch (NeurIPS 2020)

PyTorch implementation of "STNs" and "Delta-STNs".

PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)

Implement of DiGCN, NeurIPS-2020

[NeurIPS2020] The official repository of "AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows".

Official PyTorch (Lightning) implementation of the NeurIPS 2020 paper "Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity".

The implementation of paper "Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks"

A list of all papers related to anomaly detection in NeurIPS 2020.