hamedmx

TorchCP

A Python toolbox for conformal prediction research on deep learning models, using PyTorch.

nn-zero-to-hero

Neural Networks: Zero to Hero

aistats2024

May 2 - May 4, Valencia, Spain

ImageNetV2_pytorch

ImageNetV2 Pytorch Dataset

awesome-conformal-prediction

A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.

conformal-prediction

Lightweight, useful implementation of conformal prediction on real data.

VectorWorkshop

conformal_classification

Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).

deep_learning_lectures-labs

Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris

book

A textbook on informal homotopy type theory

logitnorm_ood

Official code for ICML 2022: Mitigating Neural Network Overconfidence with Logit Normalization

awesome-uncertainty-deeplearning

This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.

Proof-of-Learning

federated-learning-with-pytorch

uncertainty-toolbox

Uncertainty Toolbox: a python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

deep-learning-uncertainty

Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.

Dada

source code of [Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs](http://proceedings.mlr.press/v108/zantedeschi20a.html)

ontology-alignment-project

Ontology Alignment Using GNN Project for EE8209 - Intelligent Systems Graduate Coursework at Ryerson University, Toronto, ON

uncertainty-baselines

High-quality implementations of standard and SOTA methods on a variety of tasks.

ml-papers

Summaries of papers on machine learning, computer vision etc.

ppuda

Code for Parameter Prediction for Unseen Deep Architectures (NeurIPS 2021)

FedEM

Official code for "Federated Multi-Task Learning under a Mixture of Distributions" (NeurIPS'21)

t81_558_deep_learning

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

evidential_dl

Network-Intrusion-Detection-Using-Machine-Learning

A Novel Statistical Analysis and Autoencoder Driven Intelligent Intrusion Detection Approach

privacy

Library for training machine learning models with privacy for training data

interpret

Fit interpretable models. Explain blackbox machine learning.

evidential-deep-learning

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

gretel-synthetics

Synthetic data generators for structured and unstructured text, featuring differentially private learning.

CBL-Mariner

Linux OS for Azure 1P services and edge appliances