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07/26/2023
Simulation-based Inference for Cardiovascular Models
Over the past decades, hemodynamics simulators have steadily evolved and...
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02/08/2022
Robust Hybrid Learning With Expert Augmentation
Hybrid modelling reduces the misspecification of expert models by combin...
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06/29/2021
Diffusion Priors In Variational Autoencoders
Among likelihood-based approaches for deep generative modelling, variati...
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06/06/2021
Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks
The distributional reinforcement learning (RL) approach advocates for re...
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05/28/2021
A Probabilistic Forecast-Driven Strategy for a Risk-Aware Participation in the Capacity Firming Market
The core contribution is to propose a probabilistic forecast-driven stra...
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11/11/2020
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference
We revisit empirical Bayes in the absence of a tractable likelihood func...
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10/24/2020
Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization
Gravitational waves from compact binaries measured by the LIGO and Virgo...
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06/03/2020
Graphical Normalizing Flows
Normalizing flows model complex probability distributions by combining a...
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06/01/2020
You say Normalizing Flows I see Bayesian Networks
Normalizing flows have emerged as an important family of deep neural net...
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08/14/2019
Unconstrained Monotonic Neural Networks
Monotonic neural networks have recently been proposed as a way to define...
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11/30/2018