793 citations
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8 papers · 1 filter
Tailored Architectures for Time Series Forecasting: Evaluating Deep Learning Models on Gaussian Process-Generated Data
Victoria Hankemeier, Malte Schilling
Developments in Deep Learning have significantly improved time series forecasting by enabling more accurate modeling of complex temporal dependencies inherent in sequential data. T…
Early Detection of Forest Calamities in Homogeneous Stands -- Deep Learning Applied to Bark-Beetle Outbreaks
Maximilian Kirsch, Jakob Wernicke, Pawan Datta +1
Climate change has increased the vulnerability of forests to insect-related damage, resulting in widespread forest loss in Central Europe and highlighting the need for effective, c…
A Masked language model for multi-source EHR trajectories contextual representation learning
Ali Amirahmadi, Mattias Ohlsson, Kobra Etminani +2
Using electronic health records data and machine learning to guide future decisions needs to address challenges, including 1) long/short-term dependencies and 2) interactions betwe…
Beyond Distribution Shift: Spurious Features Through the Lens of Training Dynamics
Nihal Murali, Aahlad Puli, Ke Yu +2
Deep Neural Networks (DNNs) are prone to learning spurious features that correlate with the label during training but are irrelevant to the learning problem. This hurts model gener…
Label Propagation for Learning with Label Proportions
Rafael Poyiadzi, Raul Santos-Rodriguez, Niall Twomey
Learning with Label Proportions (LLP) is the problem of recovering the underlying true labels given a dataset when the data is presented in the form of bags. This paradigm is parti…
Relaxed Quantization for Discretized Neural Networks
Christos Louizos, Matthias Reisser, Tijmen Blankevoort +2
Neural network quantization has become an important research area due to its great impact on deployment of large models on resource constrained devices. In order to train networks…