Msc Thesis turned working paper on the applications of conformal prediction in an HFT setting for better model calibration and uncertainty quantification.

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

Kolmogorov Arnold Networks

A Python 3 package for identifying distribution shifts (a.k.a feature-shifts) between datasets. Official implementation of the paper: "iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Add…

relplot: Utilities for measuring calibration and plotting reliability diagrams

python implementation of Peng Ding's "First Course in Causal Inference"

Repository that goes with "Explanation Shift: How Did the Distribution Shift Impact the Model ?" Mougan et al. 2023

Python-based Derivative-Free Optimization with Bound Constraints

Winning submissions of Imperial College Algothon 2023

Notes, exercises and other materials related to causal inference, causal discovery and causal ML.

Course materials for Introduction to Time Series, Fall 2023

Course materials for Advanced Topics in Statistical Learning, Spring 2023

The Short-Term Predictability of Returns in Order Book Markets: A Deep Learning Perspective.

Code repository accompanying my bachelor thesis "Benchmarking conformal prediction methods for time series regression"

Paper HeteroskedasticConformalRegression

This repo contains material for the paper "Returning the Favour: When Regression Benefits from Probabilistic Causal Knowledge" ICML 2023 paper

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

Code for "Kernel methods are competitive for operator learning" Battle, Darcy. Hosseini and Owhadi.

Lightweight, useful implementation of conformal prediction on real data.

Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, calibration, etc

The repository for the Machine Learning and Big Data with kdb+/q book by Novotny et al.

Python implementation of Kernel Maximum Moment Restriction for Instrumental Variable Regression

Code of PriorVAE: encoding spatial priors with variational autoencoders

A unified framework for machine learning with time series

Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems

Causal Discovery for Python. Translation and extension of the Tetrad Java code.