cuola

cuola's Stars

• alan-turing-institute/TCPDBench

  The Turing Change Point Detection Benchmark: An Extensive Benchmark Evaluation of Change Point Detection Algorithms on real-world data

  13127

• jswu18/distribution-discrepancies

  Maximum Mean Discrepancy (MMD), Kernel Stein Discrepancy (KSD), and Fisher Divergence

  Language:Jupyter Notebook122

• Heimine/NC_MLab

  Neural Collapse in Multi-label Learning with Pick-all-label Loss

  Language:Jupyter Notebook4

• wgrathwohl/LSD

  Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"

  Language:Python455

• Project-MONAI/tutorials

  MONAI Tutorials

  Language:Jupyter Notebook1.8k668

• Project-MONAI/MONAI

  AI Toolkit for Healthcare Imaging

  Language:Python5.7k1.1k

• Project-MONAI/GenerativeModels

  MONAI Generative Models makes it easy to train, evaluate, and deploy generative models and related applications

  Language:Jupyter Notebook60087

• zhenzhel/lift_map_detect

  The official code release for Unsupervised Out-of-distribution Detection with Diffusion Inpainting (ICML 2023)

  Language:Python231

• marksgraham/ddpm-ood

  Official PyTorch code for "Out-of-distribution detection with denoising diffusion models"

  Language:Python426

• deepcharles/ruptures

  ruptures: change point detection in Python

  Language:Python1.6k163

• OctoberChang/klcpd_code

  Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)

  Language:Python5813

• deryckt/TIRE

  Autoencoder-based Change Point Detection in Time Series Data using a Time-Invariant Representation

  Language:Jupyter Notebook377

• cruiseresearchgroup/TSCP2

  Time Series Change Point Detection based on Contrastive Predictive Coding

  Language:Python7217

• Jieli12/AutoCPD

  Language:PureBasic92

• vkhamesi/ocpdet

  📦 A Python package for online changepoint detection, implementing state-of-the-art algorithms and a novel approach based on neural networks.

  Language:Python222

• shirara1016/si_for_cpd_by_rnn

  Language:Python21

• xiuheng-wang/NODE_release

  Codes for the paper "Change Point Detection with Neural Online Density-ratio Estimator" (ICASSP 2023).

  Language:Python41

• zahraatashgahi/ALACPD

  Change-point detection using neural networks

  Language:Python174

• isl-org/MultiObjectiveOptimization

  Source code for Neural Information Processing Systems (NeurIPS) 2018 paper "Multi-Task Learning as Multi-Objective Optimization"

  Language:Python977171

• shaohua0116/MultiDigitMNIST

  Combine multiple MNIST digits to create datasets with 100/1000 classes for few-shot learning/meta-learning

  Language:Python9217

• tmlr-group/class_prior

  [ICML 2023] "Detecting Out-of-distribution Data through In-distribution Class Prior"

  Language:Python7

• Jingkang50/OpenOOD

  Benchmarking Generalized Out-of-Distribution Detection

  Language:Python843107

• gpleiss/temperature_scaling

  A simple way to calibrate your neural network.

  Language:Python1.1k159

• Renchunzi-Xie/Dispersion

  Language:Python1

• yaodongyu/ProjNorm

  Predicting Out-of-Distribution Error with the Projection Norm

  Language:Python171

• saurabhgarg1996/ATC_code

  Code and results accompanying our paper titled Leveraging Unlabeled Data to Predict Out-of-Distribution Performance at ICLR 2022

  Language:Python10

• YuheD/awesome-model-transferability-estimation

  A collection of model transferability estimation methods.

  191

• xqsi/iGAT

  Language:Python1

• fra31/auto-attack

  Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"

  Language:Python646112

• RobustBench/robustbench

  RobustBench: a standardized adversarial robustness benchmark [NeurIPS 2021 Benchmarks and Datasets Track]

  Language:Python65599