geyh96

LaTeX-OCR

pix2tex: Using a ViT to convert images of equations into LaTeX code.

ddim

Denoising Diffusion Implicit Models

DRL-Pytorch

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

OptML_course

EPFL Course - Optimization for Machine Learning - CS-439

Diffusion-Models-pytorch

Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)

normalizing-flows

PyTorch implementation of normalizing flow models

causal-ml

Must-read papers and resources related to causal inference and machine (deep) learning

TorchCP

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

conformal

Tools for conformal inference in regression

DeepRL_PyTorch

Deep Reinforcement Learning codes for study. Currently, there are only codes for algorithms: DQN, C51, QR-DQN, IQN, QUOTA.

denoising-diffusion-model

A simple guide to diffusion models. Helpful in understanding the concept and practicing with the method.

CATENets

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

aciccomp

Code to run submissions for the Atlantic Causal Inference Competition

ReHLine

Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence

OfflineRLReadingGroup

Offline Reinforcement Learning Reading Group

Causal4Application

circe

Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)

AgeFlow

AgeFlow: Conditional Age Progression and Regression with Normalizing Flows (IJCAI 2021)

functional_diffusion

conquer

Convolution Smoothed Quantile Regression

ANN2

Neural Networks package for R with a fast C++ back-end and special support for unsupervised anomaly detection using autoencoders

atlantic-causal-2017

Targeted Learning entry in the Atlantic Causal Inference Conference's 2017 competition

cfcausalPaper

Paper Repository

tmp_model

Compensates limited data, batch-effects, and technological heterogeneity in single-cell sequencing

stan-docs

Documentation for the Stan language and CmdStan

qrLOFT

Lack of Fit Tests for Low and High Dimensional Quantile Regression Model

gcdl

Uncertainty quantification in high-dimensional linear models incorporating graphical structures with applications to gene set analysis.

DeepRL-Tutorials

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

OnlineDSGD

This repository includes source codes for debiased stochastic gradient descent algorithms for online statistical inference with high-dimensional streaming data.

CAESAR.Suite_Analysis

CAESAR suite is an open-source software package that provides image-based spatial co-embedding of locations and genomic features.