Artificial intelligence (AI) can be trained to recognize whether a tissue image contains a tumor. However, exactly how it makes its decision has remained a mystery until now. A team from the Research Center for Protein Diagnostics (PRODI) at Ruhr-Universität Bochum is developing a new approac...
Considerations for applying logical reasoning to explain neural network outputsFederico Maria CauLucio Davide SpanoNava TintarevCEUR-WS2020 Italian Workshop on Explainable Artificial Intelligence, XAI.it 2020
Avengers: Age of Ultron pits the titular heroes against a sentient artificial intelligence, and smart money says that it could soar at the box office to be the highest-grossing film of the introduction into the Marvel cinematic universe, it's possible, though Marvel Studios boss Kevin Feige tol...
That younger individuals perceive the world as moving slower than adults is a familiar phenomenon. Yet, it remains an open question why that is. Using event segmentation theory, electroencephalogram (EEG) beamforming and nonlinear causal relationship estimation using artificial neural network methods, we...
Artificial neural networks (brain-like computer models that can reliably recognize patterns, such as word sounds, after exhaustive training). In practice, the everyday speech recognition we encounter in things like automated call centers, computer dictationsoftware, or smartphone "agents" (like Siri ...
[2] Vinogradova, Kira, Alexandr Dibrov, and Gene Myers. “Towards Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping.”Proceedings of the AAAI Conference on Artificial Intelligence34, no. 10 (April 2020): 13943–13944, https://doi.org/10.1609/aaai.v34i10.7244. ...
In his book The Global Brain Awakens: Our Next Evolutionary Leap, Russell suggested that a fizzing global network of densely interconnected humans would form the springboard for the next stage in human development [2], although artificial intelligence researcher Mark Humphrys dismisses such simple ...
Explainable Artificial Intelligence for Cotton Yield Prediction With Multisource Data Monotone Tree-Based GAMI Models by Adapting XGBoost Neural Graphical Models FAST: An Optimization Framework for Fast Additive Segmentation in Transparent ML The Quantitative Analysis of Explainable AI for Network Anomaly Dete...
{Purifying interaction effects with the functional anova: An efficient algorithm for recovering identifiable additive models}, author={Lengerich, Benjamin and Tan, Sarah and Chang, Chun-Hao and Hooker, Giles and Caruana, Rich}, booktitle={International Conference on Artificial Intelligence and ...
A Neural Network Walks into a Lab: Towards Using Deep Nets as Models for Human Behaviour, 1–39 (2020). Perconti, P. & Plebe, A. Deep learning and cognitive science. Cognition 203, 104365 (2020). Article Google Scholar Miller, T. Explanation in artificial intelligence: Insights from the...