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Found 8 papers, 2 papers with code
Generative models for wearables data
Data scarcity is a common obstacle in medical research due to the high costs associated with data collection and the complexity of gaining access to and utilizing data.
GENNI: Visualising the Geometry of Equivalences for Neural Network Identifiability
We propose an efficient algorithm to visualise symmetries in neural networks.
Patch-based Brain Age Estimation from MR Images
Many studies have been proposed for the prediction of chronological age from brain MRI using machine learning and specifically deep learning techniques.
Biologically inspired architectures for sample-efficient deep reinforcement learning
Deep reinforcement learning requires a heavy price in terms of sample efficiency and overparameterization in the neural networks used for function approximation.
How to Incorporate Monotonicity in Deep Networks While Preserving Flexibility?
We focus on incorporating monotonic trends, and propose a novel gradient-based point-wise loss function for enforcing partial monotonicity with deep neural networks.
Adaptive Model Selection Framework: An Application to Airline Pricing
Multiple machine learning and prediction models are often used for the same prediction or recommendation task.
Tensor Dropout for Robust Learning
CNNs achieve remarkable performance by leveraging deep, over-parametrized architectures, trained on large datasets.
Dynamic Pricing for Airline Ancillaries with Customer Context
We also measure the real-world business impact of these approaches by deploying them in an A/B test on an airline's internet booking website.
