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04/26/2023
AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires
Recent advances in immunomics have shown that T-cell receptor (TCR) sign...
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02/25/2022
Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations
End-to-end learning of dynamical systems with black-box models, such as ...
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05/28/2019
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems
We introduce a flexible, scalable Bayesian inference framework for nonli...
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10/09/2018
Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks
Bayesian neural networks (BNNs) hold great promise as a flexible and pri...
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02/13/2017
Soft Weight-Sharing for Neural Network Compression
The success of deep learning in numerous application domains created the...
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06/28/2016
Automatic Variational ABC
Approximate Bayesian Computation (ABC) is a framework for performing lik...
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06/11/2015
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference
We describe an embarrassingly parallel, anytime Monte Carlo method for l...
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03/06/2015
Hamiltonian ABC
Approximate Bayesian computation (ABC) is a powerful and elegant framewo...
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12/09/2014
POPE: Post Optimization Posterior Evaluation of Likelihood Free Models
In many domains, scientists build complex simulators of natural phenomen...
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12/08/2014
MLitB: Machine Learning in the Browser
With few exceptions, the field of Machine Learning (ML) research has lar...
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01/13/2014
