SHMILY-Programmer

SHMILY-Programmer's Stars

• h-yu16/Sparse_Variable_Independence

  Official repo for AAAI 2023 paper "Stable Learning via Sparse Variable Independence".

  Language:Python12

• xxgege/NICO-plus

  The Official Repository for CVPR2023 Paper "NICO++: Towards Better Benchmarking for Domain Generalization".

  Language:Python343

• WilliamBUG/TIVA

  The implementation of TIVA

  Language:Python8

• googlebaba/StableGNN

  StableGNN-Generalizing Graph Neural Networks on Out-Of-Distribution Graphs

  Language:Python183

• x-zho14/MAPLE

  Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning

  Language:Python411

• xxgege/StableNet

  Official repository for CVPR21 paper "Deep Stable Learning for Out-Of-Distribution Generalization".

  Language:Python18443

• iancovert/sage

  For calculating global feature importance using Shapley values.

  Language:Python24534

• KindXiaoming/pykan

  Kolmogorov Arnold Networks

  Language:Jupyter Notebook14.7k1.3k

• Silver-Shen/Stable_Linear_Model_Learning

  The implementation and addtional material of AAAI2020 paper "Stable Learning via Sample Reweighting"

  Language:Python167

• LFhase/FeAT

  [NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization

  Language:Python241

• cauchyturing/Imaging-time-series-to-improve-classification-and-imputation

  Python 3.6+ (only)

  Language:Python10956

• Master-PLC/FreDF

  Repository for "FreDF: Learning to Forecast in the Transformed Domain"

  Language:Shell514

• tankwin08/Bayesian_uncertainty_LSTM

  Bayesian, Uncertainty, Neutral Networks, LSTM, time series

  Language:Jupyter Notebook327

• kumar-shridhar/PyTorch-BayesianCNN

  Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

  Language:Python1.4k323

• aikunyi/FourierGNN

  Official implementation of the paper "FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective"

  Language:Python16015

• ZheyuAqaZhang/UnbiasedGBM

  repository for Unbiased Gradient Boosting Decision Tree with Unbiased Feature Importance

  Language:Jupyter Notebook273

• jarrycyx/UNN

  Causal Neural Nerwork

  Language:Jupyter Notebook769

• yandex-research/tabular-dl-tabr

  The implementation of "TabR: Unlocking the Power of Retrieval-Augmented Tabular Deep Learning"

  Language:Python25727

• EtashGuha/R2CCP

  Language:Python175

• MAGICS-LAB/BiSHop

  [ICML 2024] BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model

  Language:Python6

• seedatnabeel/TRIAGE

  TRIAGE: Characterizing and auditing training data for improved regression (NeurIPS 2023)

  Language:Jupyter Notebook73

• deargen/MT-ENet

  Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022

  Language:Python181

• NVlabs/pac-bayes-conformal-prediction

  PAC-Bayes generalization certificates for ICP

  Language:Jupyter Notebook172

• SJYuCNEL/Cauchy-Schwarz-Information-Bottleneck

  Cauchy-Schwarz divergence Information Bottleneck

  Language:Python61

• drewprinster/conformal-mfcs

  Code for multistep feedback covariate shift conformal prediction experiments in "Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them)" (ICML 2024)

  Language:Jupyter Notebook231

• ztxtech/Time-Evidence-Fusion-Network

  Official implementation of "Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting" (https://arxiv.org/abs/2405.06419)

  Language:Python584

• FlynnYe/UR-ERN

  Repository for "Uncertainty Regularized Evidential Regression" published in AAAI 2024

  Language:Jupyter Notebook9

• CAMP-eXplain-AI/InputIBA

  NeurIPS 2021 | Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information

  Language:Python324

• marcotcr/lime

  Lime: Explaining the predictions of any machine learning classifier

  Language:JavaScript11.5k1.8k

• hsndbk4/GDWS

  Code for the paper titled "Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks" (NeurIPS 2021 Spotlight).

  Language:Python103