seedatnabeel

3S-Testing

Data-IQ

Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data (NeurIPS 2022)

Data-SUITE

Data-SUITE: Data-centric identification of in-distribution incongruous examples (ICML 2022)

H-CAT

Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI (ICLR 2024)

Inverted-Pendulum-Control

Variety of controller designs for a single and double inverted pendulum on a cart

Pygotham2019_GANS

Tutorial on Generative Adversarial Networks (GAN) at Pygotham NYC 2019

SSCP

SSCP: Improving Adaptive Conformal Prediction Using Self-supervised Learning (AISTATS 2023)

TE-CDE

Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)

TRIAGE

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

Uncertainty-Decision-Support-Healthcare

MCU-Net: A framework towards uncertainty representations for decision support system patient referrals in healthcare contexts (KDD 2020, ICML UDL 2020)

seedatnabeel/TE-CDE

Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)

seedatnabeel/SSCP

SSCP: Improving Adaptive Conformal Prediction Using Self-supervised Learning (AISTATS 2023)

seedatnabeel/Data-IQ

Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data (NeurIPS 2022)

seedatnabeel/Data-SUITE

Data-SUITE: Data-centric identification of in-distribution incongruous examples (ICML 2022)

seedatnabeel/TRIAGE

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

seedatnabeel/Uncertainty-Decision-Support-Healthcare

MCU-Net: A framework towards uncertainty representations for decision support system patient referrals in healthcare contexts (KDD 2020, ICML UDL 2020)

seedatnabeel/Inverted-Pendulum-Control

Variety of controller designs for a single and double inverted pendulum on a cart

seedatnabeel/Pygotham2019_GANS

Tutorial on Generative Adversarial Networks (GAN) at Pygotham NYC 2019

seedatnabeel/3S-Testing

seedatnabeel/covid_19_chatbot

Covid-19 Chatbot is a multi-lingual WhatsApp chatbot to answer FAQs about Covid-19 as per the WHO. It also has computer vision capabilities allowing a WhatsApp client to send a picture of a mask and the chatbot will classify the mask as either a N95, surgical or cloth mask.

seedatnabeel/Data-Imputation-Uncertainty

Implementation of work on uncertainty for data imputation

seedatnabeel/H-CAT

Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI (ICLR 2024)

seedatnabeel/CATENets

Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.

seedatnabeel/Datasets

seedatnabeel/Dig-Dug-C-Game

A clone of the Dig Dug Arcade Game using C++ & SFML

seedatnabeel/fisiquimicamente

FisiQuímicamente / PhysiChemically / FisiQuímicament

seedatnabeel/hugo-resource-images

Example Project to show how to access page image resources from another location in Hugo

seedatnabeel/label-studio

Label Studio is a multi-type data labeling and annotation tool with standardized output format

seedatnabeel/OTC

Repository for GSL 2016

seedatnabeel/OTC-Deploy

seedatnabeel/OTC-Repo

seedatnabeel/seedatnabeel.github.io

seedatnabeel/Simplex

This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help of a corpus of examples. For more details, please read our NeurIPS 2021 paper: 'Explaining Latent Representations with a Corpus of Examples'.

seedatnabeel/synthcity

A library for generating and evaluating synthetic tabular data for privacy, fairness and data augmentation.

seedatnabeel/UQ360

Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.

seedatnabeel/wowchemy-hugo-themes

🔥 Hugo website builder, Hugo themes & Hugo CMS. No code, easily build with blocks! 创建在线课程，学术简历或初创网站。#OpenScience