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07/11/2023
Benchmarking Algorithms for Federated Domain Generalization
While prior domain generalization (DG) benchmarks consider train-test da...
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06/20/2023
Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models
Learning latent causal models from data has many important applications ...
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02/28/2023
Towards Enhanced Controllability of Diffusion Models
Denoising Diffusion models have shown remarkable capabilities in generat...
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10/19/2022
Towards Explaining Distribution Shifts
A distribution shift can have fundamental consequences such as signaling...
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07/05/2022
Cooperative Distribution Alignment via JSD Upper Bound
Unsupervised distribution alignment estimates a transformation that maps...
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07/04/2022
Discrete Tree Flows via Tree-Structured Permutations
While normalizing flows for continuous data have been extensively resear...
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07/14/2021
Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests
While previous distribution shift detection approaches can identify if a...
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04/15/2021
Iterative Barycenter Flows
The task of mapping two or more distributions to a shared representation...
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04/06/2021
Shapley Explanation Networks
Shapley values have become one of the most popular feature attribution e...
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12/24/2020
Exploring Adversarial Examples via Invertible Neural Networks
Adversarial examples (AEs) are images that can mislead deep neural netwo...
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12/02/2019
Diagnostic Curves for Black Box Models
In safety-critical applications of machine learning, it is often necessa...
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08/31/2016
A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution
The Poisson distribution has been widely studied and used for modeling u...
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06/02/2016
Generalized Root Models: Beyond Pairwise Graphical Models for Univariate Exponential Families
We present a novel k-way high-dimensional graphical model called the Gen...
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03/11/2016
