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05/31/2023
Protein Design with Guided Discrete Diffusion
A popular approach to protein design is to combine a generative model wi...
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10/22/2022
Bayesian Optimization with Conformal Coverage Guarantees
Bayesian optimization is a coherent, ubiquitous approach to decision-mak...
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10/08/2022
PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design
Bayesian optimization offers a sample-efficient framework for navigating...
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03/23/2022
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders
Bayesian optimization is a gold standard for query-efficient continuous ...
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02/10/2022
Deconstructing the Inductive Biases of Hamiltonian Neural Networks
Physics-inspired neural networks (NNs), such as Hamiltonian or Lagrangia...
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10/28/2021
Conditioning Sparse Variational Gaussian Processes for Online Decision-making
With a principled representation of uncertainty and closed form posterio...
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06/10/2021
Does Knowledge Distillation Really Work?
Knowledge distillation is a popular technique for training a small stude...
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03/02/2021
Kernel Interpolation for Scalable Online Gaussian Processes
Gaussian processes (GPs) provide a gold standard for performance in onli...
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08/28/2020
On the model-based stochastic value gradient for continuous reinforcement learning
Model-based reinforcement learning approaches add explicit domain knowle...
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02/25/2020