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Found 9 papers, 3 papers with code
The NVIDIA PilotNet Experiments
Four years ago, an experimental system known as PilotNet became the first NVIDIA system to steer an autonomous car along a roadway.
Invertible Autoencoder for domain adaptation
However, it does not explicitly enforce $F_{BA}$ to be an inverse operation to $F_{AB}$.
Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car
This eliminates the need for human engineers to anticipate what is important in an image and foresee all the necessary rules for safe driving.
VisualBackProp: efficient visualization of CNNs
We furthermore justify our approach with theoretical arguments and theoretically confirm that the proposed method identifies sets of input pixels, rather than individual pixels, that collaboratively contribute to the prediction.
Structured adaptive and random spinners for fast machine learning computations
We consider an efficient computational framework for speeding up several machine learning algorithms with almost no loss of accuracy.
On the boosting ability of top-down decision tree learning algorithm for multiclass classification
We analyze the performance of the top-down multiclass classification algorithm for decision tree learning called LOMtree, recently proposed in the literature Choromanska and Langford (2014) for solving efficiently classification problems with very large number of classes.
End to End Learning for Self-Driving Cars
The system automatically learns internal representations of the necessary processing steps such as detecting useful road features with only the human steering angle as the training signal.
Binary embeddings with structured hashed projections
We prove several theoretical results showing that projections via various structured matrices followed by nonlinear mappings accurately preserve the angular distance between input high-dimensional vectors.
Differentially- and non-differentially-private random decision trees
We consider supervised learning with random decision trees, where the tree construction is completely random.
