News: 3 new papers accepted at ICML 2020  →

XaiPient enables trustworthy and robust AI

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We are proud to be accepted into these accelerators for 2020-2021: CDL AI Stream and Nvidia Inception

Papers & Articles

NEW → Concise Explanations of Neural Networks using Adversarial Training (ICML 2020)
NEW → CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods (ICML 2020)
NEW → Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models (ICML 2020)
Explainability in Deep Neural Networks, Parts 1-4
Robust Attribution Regularization (NeurIPS 2019)

About us

XaiPient is fundamentally re-imagining AI explainability with the human end-user in mind. The co-founders are two CMU PhDs (in CS and ML) who are active in Explainability research, and have a combined four decades of research and industry experience in Security and Machine Learning.


Our technology leverages algorithms and human-centric design to automatically generate high-level, domain-specific, actionable explanations. The explanations combine narratives and visuals and are tailored to the technical expertise of the audience.


An API aimed at Data Scientists and ML Engineers. A polished SAAS (Software As A Service) product aimed at non-technical end-users. Consulting services to work closely with businesses to integrate our technology into their ML workflows.
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