Statistics for topic explainable-ai

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

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

Shapley Interactions for Machine Learning

High-Performance Symbolic Regression in Python and Julia

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

Shapley Interactions for Machine Learning

A list of (post-hoc) XAI for time series

Different SHAP algorithms

PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)

Causal discovery algorithms and tools for implementing new ones

Shapley Interactions for Machine Learning

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

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

High-Performance Symbolic Regression in Python and Julia

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

Shapley Interactions for Machine Learning

A list of (post-hoc) XAI for time series

Different SHAP algorithms

PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)

Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.

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

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

High-Performance Symbolic Regression in Python and Julia

Shapley Interactions for Machine Learning

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

Shapley Interactions for Machine Learning

[EMNLP 2024] The official GitHub repo for the survey paper "Knowledge Conflicts for LLMs: A Survey"

A list of (post-hoc) XAI for time series

Bias-to-Text: Debiasing Unknown Visual Biases through Language Interpretation

SIDU: SImilarity Difference and Uniqueness method for explainable AI

Shapley Interactions for Machine Learning

Code for ACL 2024 paper "TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space"

[EMNLP'2024] "XRec: Large Language Models for Explainable Recommendation"

A list of (post-hoc) XAI for time series

Mechanistically interpretable neurosymbolic AI (Nature Comput Sci 2024): losslessly compressing NNs to computer code and discovering new algorithms which generalize out-of-distribution and outperform ...

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

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

High-Performance Symbolic Regression in Python and Julia

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

ICCV 2023 Papers: Discover cutting-edge research from ICCV 2023, the leading computer vision conference. Stay updated on the latest in computer vision and deep learning, with code included. ⭐ support ...

[ICLR 2024 Oral] Less is More: Fewer Interpretable Region via Submodular Subset Selection

[CIKM'2023] "STExplainer: Explainable Spatio-Temporal Graph Neural Networks"

source code for USENIX Security paper xNIDS

Carefully curated list of awesome data science resources.

SIDU: SImilarity Difference and Uniqueness method for explainable AI