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python tools to check recourse in linear classification
Code for the paper "PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning" by L. Corbucci, M. A. Heikkilä, D.S. Noguero, A. Monreale, N. Kourtellis.
source code for KDD'22 paper "Learning Fair Representation via Distributional Contrastive Disentanglement"
Causal Variational AutoEncoders
🐯 Sara - the Rasa Demo Bot: An example of a contextual AI assistant built with the open source Rasa Stack
BlueBERT, pre-trained on PubMed abstracts and clinical notes (MIMIC-III).
PyTorch Implementation of Rasa's DIET Classifier.
Bioinformatics'2020: BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Noise removal/ reducer from the audio file in python. De-noising is done using Wavelets and thresholding is done by VISU Shrink thresholding technique
API & Webapp to answer questions about COVID-19. Using NLP (Question Answering) and trusted data sources.
SPEAR-ASR and SPEAR-WakeUp Software Development Kit in Python for Linux
🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
SPEAR-ASR and SPEAR-WakeUp Software Development Kit for Android
This repo contains the public directory which is the blog
This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence Functions by Pang Wei Koh and Percy Liang.
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Causal Inference and Discovery in Python by Packt Publishing
This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence Functions by Pang Wei Koh and Percy Liang.
Implementation of Estimating Training Data Influence by Tracing Gradient Descent (NeurIPS 2020)
Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"
Pytorch implementation of VAEs for heterogeneous likelihoods.
Pytorch implementation of VAEs for heterogeneous likelihoods.
Categorical Variational Autoencoders
Causal Effect Inference with Deep Latent-Variable Models
Simple and clean implementation of Conditional Variational AutoEncoder (CVAE) using PyTorch
IRT ideal point models in R using Stan and JAGS