(ICML 2023) High Fidelity Image Counterfactuals with Probabilistic Causal Models

Implementation of DATS -- Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks -- ICLR 2024

Official Pytorch implementation of ReBias (Learning De-biased Representations with Biased Representations), ICML 2020

Combating hidden stratification with GEORGE

Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

Model Patching: Closing the Subgroup Performance Gap with Data Augmentation

A playbook for systematically maximizing the performance of deep learning models.

Official code repository for Correct-N-Contrast

Attend Infer Repeat (AIR) in PyTorch

📝 An awesome Data Science repository to learn and apply for real world problems.

Burgess et al. "MONet: Unsupervised Scene Decomposition and Representation"

Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)