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Found 9 papers, 0 papers with code
Masked Multi-Step Probabilistic Forecasting for Short-to-Mid-Term Electricity Demand
Models trainded with MMMPF can also generate desired quantiles to capture uncertainty and enable probabilistic planning for grid of the future.
Masked Multi-Step Multivariate Time Series Forecasting with Future Information
Furthermore, once a neural network model is trained with MMMF, its inference speed is similar to that of the same model trained with traditional regression formulations, thus making MMMF a better alternative to existing regression-trained time series forecasting models if there is some available future information.
Uncertainty-aware Perception Models for Off-road Autonomous Unmanned Ground Vehicles
We test the hypothesis that model trained on a single dataset may not generalize to other off-road navigation datasets and new locations due to the input distribution drift.
Automated Creation and Human-assisted Curation of Computable Scientific Models from Code and Text
Scientific models hold the key to better understanding and predicting the behavior of complex systems.
Adversarial Attacks with Time-Scale Representations
Third, we generate new adversarial images by projecting back the original coefficients from the low scale and the perturbed coefficients from the high scale sub-space.
Variational Encoder-based Reliable Classification
Machine learning models provide statistically impressive results which might be individually unreliable.
Justification-Based Reliability in Machine Learning
To address this need, we link the question of reliability of a model's individual prediction to the epistemic uncertainty of the model's prediction.
Design of intentional backdoors in sequential models
Recent work has demonstrated robust mechanisms by which attacks can be orchestrated on machine learning models.
Symbolic Analysis-based Reduced Order Markov Modeling of Time Series Data
In the second example, the data set is taken from NASA's data repository for prognostics of bearings on rotating shafts.
