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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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10/20/2022
On Feature Learning in the Presence of Spurious Correlations
Deep classifiers are known to rely on spurious features x2013 patterns w...
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10/06/2022
The Lie Derivative for Measuring Learned Equivariance
Equivariance guarantees that a model's predictions capture key symmetrie...
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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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03/21/2020
Adaptive Informative Path Planning with Multimodal Sensing
Adaptive Informative Path Planning (AIPP) problems model an agent tasked...
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05/31/2019
Using Latent Variable Models to Observe Academic Pathways
Understanding large-scale patterns in student course enrollment is a pro...
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06/29/2018
