Graph neural networksResponsible artificial intelligenceUser modeling is a key topic in many applications, mainly social networks and information retrieval systems. To assess the effectiveness of a user modeling approach, its capability to classify personal characteristics (e.g., the gender, age, or ...
sales development manager at Intel; Sophie Le Drew, senior advisor, Partnerships at Mila; Dan Nitta Mackay, industry technical specialist at Intel; Kavitha Prasad, vice president and general manager of Datacenter Cloud & AI Strategy and Execution at Intel; Yoshua Bengio, founder and scientific direc...
Explainable Graph Neural Networks- Blog post that provides a brief overview of XAI methods for graph neural networks (GNNs). Videos and presentations ICML 2019 session - Robust statistics and interpretability Courses Kaggle - Machine Learning Explainability- Kaggle course about the basics of XAI with ...
Tools for graph structure recovery and dependencies are included.” captum "Model interpretability and understanding for PyTorch.” causalml "Uplift modeling and causal inference with machine learning algorithms.” cdt15, Causal Discovery Lab., Shiga University "LiNGAM is a new method for estimating ...
Prompt flow allows developers to create executable flows that link LLMs, prompts, and Python tools through a visualized graph. It also enables developers to debug, share, and iterate their flows with ease through team collaboration and historical tracking. Moreover, prompt flow allows developers to...