Pinned Repositories
auton-survival
Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events
causallib
A Python package for modular causal inference analysis and model evaluations
beaglebone_mmap
Example code on accessing BeagleBone GPIO through mmap()
deep_cox_mixtures
Code for the paper "Deep Cox Mixtures for Survival Regression", Machine Learning for Healthcare Conference 2021
fb-sentimentaliser
Keep Track of your friends' sentiment!
sat-light
sentiband
The HairBand that knows your Mood!
simple-DBScan
A Simple Python Implementation of DBScan
speedtester
A Python script to check the internet speeds during the day and graph the readings
google-research
Google Research
chiragnagpal's Repositories
chiragnagpal/deep_cox_mixtures
Code for the paper "Deep Cox Mixtures for Survival Regression", Machine Learning for Healthcare Conference 2021
chiragnagpal/fb-sentimentaliser
Keep Track of your friends' sentiment!
chiragnagpal/sentiband
The HairBand that knows your Mood!
chiragnagpal/Active-Search
chiragnagpal/ActiveSearch
Active Search with Concept Graph generated with Knowledge Bases
chiragnagpal/anonymous-survival
Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events
chiragnagpal/auton_survival
Package for performing Time-to-Event prediction and Survival Analysis.
chiragnagpal/calibration
Code implementing "A Calibration Metric for Risk Scores with Survival Data" (MLHC 2019)
chiragnagpal/causallib
A Python package for modular causal inference analysis and model evaluations
chiragnagpal/chiragnagpal.github.io
chiragnagpal/cmuwebsite
chiragnagpal/codemod
Codemod is a tool/library to assist you with large-scale codebase refactors that can be partially automated but still require human oversight and occasional intervention. Codemod was developed at Facebook and released as open source.
chiragnagpal/counterfactual_survival_analysis
ACM CHIL 2021: "Enabling Counterfactual Survival Analysis with Balanced Representations"
chiragnagpal/edge-of-stability
chiragnagpal/google-research
Google Research
chiragnagpal/hl4ai
chiragnagpal/longitudinal_survival_phenotyping
chiragnagpal/noisy-neural-training
Noisy Neural training allows training neural networks that do not overfit.
chiragnagpal/personaLink
Package to perform persona linking (MEMEX 16 CP2)
chiragnagpal/probflow
A Python package for building Bayesian models with TensorFlow or PyTorch
chiragnagpal/proxygen
A collection of C++ HTTP libraries including an easy to use HTTP server.
chiragnagpal/pycox
Survival analysis with PyTorch
chiragnagpal/pyro
Deep universal probabilistic programming with Python and PyTorch
chiragnagpal/scikit-learn
scikit-learn: machine learning in Python
chiragnagpal/staging-client-java
A cancer staging client library for Java applications.
chiragnagpal/Summer_Hack_CP2
Applying Pairwise Classification and Active Search For MEMEX Summer Camp '16
chiragnagpal/Survival-Analysis-using-Deep-Learning
This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis
chiragnagpal/the-algorithm
Source code for Twitter's Recommendation Algorithm
chiragnagpal/unbiased_risk_with_proxies
chiragnagpal/uncertainty-toolbox
A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization