The title text for this comic mentionsumbrella insurance, which is what insurance companies in the United States pay when the payment extends over their own policies. It makes a joke with the isotope representation of Uranium-238 being238U, and is something that Cueball might need to consult wi...
Deep learning example with GradientExplainer (TensorFlow/Keras/PyTorch models) Expected gradients combines ideas fromIntegrated Gradients, SHAP, andSmoothGradinto a single expected value equation. This allows an entire dataset to be used as the background distribution (as opposed to a single reference ...
@inproceedings{lou2013accurate, title={Accurate intelligible models with pairwise interactions}, author={Lou, Yin and Caruana, Rich and Gehrke, Johannes and Hooker, Giles}, booktitle={Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining}, pages={623--...
3,4,5. For example, in the 2016 U. S. presidential election, each adult was shown, on average, more than one item with false content6. On top of that, there were more user interactions with deliberately false content
We find that the corresponding trends and correlations with SSTs are similar to the control experiment described in the main text. Total carbon column observing network TCCON is a global network of ground-based Fourier transform spectrometer (FTS) instruments that measure, among other compounds, the...
One problem with arguments of this kind is that they weigh up only basic economic and technological factors and fail to consider the hidden environmental costs of things like oil spills, air pollution, land destruction from coal mining, or climate change—and especially the future costs, which ar...
For example, new intake procedures have to be learnt and adverse effects evolve but no benefits in the form of health state improvements cover these costs in this phase of the treatment. When the medicine starts being efficacious, patients want their previous investments in their health to be ...
An engine needs to spin round relatively quickly to work efficiently (usually thousands of times a minute), but a car's wheels never go that fast. The power an engine can produce at any given moment may be very different from what the driver needs. For example, if you're moving off ...
plots.text(shap_values[0, :, "POSITIVE"]) Deep learning example with DeepExplainer (TensorFlow/Keras models) Deep SHAP is a high-speed approximation algorithm for SHAP values in deep learning models that builds on a connection with DeepLIFT described in the SHAP NIPS paper. The implementation ...
plots.text(shap_values[0, :, "POSITIVE"]) Deep learning example with DeepExplainer (TensorFlow/Keras models) Deep SHAP is a high-speed approximation algorithm for SHAP values in deep learning models that builds on a connection with DeepLIFT described in the SHAP NIPS paper. The implementation ...