research
∙
04/26/2023
AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires
Recent advances in immunomics have shown that T-cell receptor (TCR) sign...
share
research
∙
07/11/2022
Repairing Neural Networks by Leaving the Right Past Behind
Prediction failures of machine learning models often arise from deficien...
research
∙
02/01/2021
Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens
Major depressive disorder is a debilitating disease affecting 264 millio...
research
∙
01/13/2021
Preferential Mixture-of-Experts: Interpretable Models that Rely on Human Expertise as much as Possible
We propose Preferential MoE, a novel human-ML mixture-of-experts model t...
research
∙
12/12/2019
Towards Expressive Priors for Bayesian Neural Networks: Poisson Process Radial Basis Function Networks
While Bayesian neural networks have many appealing characteristics, curr...
research
∙
05/15/2019
Output-Constrained Bayesian Neural Networks
Bayesian neural network (BNN) priors are defined in parameter space, mak...
research
∙
11/16/2018
Latent Projection BNNs: Avoiding weight-space pathologies by learning latent representations of neural network weights
While modern neural networks are making remarkable gains in terms of pre...
research
∙
06/29/2018
Sparse Three-parameter Restricted Indian Buffet Process for Understanding International Trade
This paper presents a Bayesian nonparametric latent feature model specia...
research
∙
07/26/2017
General Latent Feature Modeling for Data Exploration Tasks
This paper introduces a general Bayesian non- parametric latent feature ...
research
∙
06/12/2017
