6 papers
Paleoclimate Boundary Conditions as an Out-of-Sample Test for the Forced Response of Ocean Climate Emulators
Adam Subel, Laure Zanna
AI weather emulators benefit from clear objectives and metrics, which have led to the rapid development of models that outperform traditional benchmarks. In contrast, long-term cli…
Your VAR Model is Secretly an Efficient and Explainable Generative Classifier
Yi-Chung Chen, David I. Inouye, Jing Gao
Generative classifiers, which leverage conditional generative models for classification, have recently demonstrated desirable properties such as robustness to distribution shifts.…
From Invariant Representations to Invariant Data: Provable Robustness to Spurious Correlations via Noisy Counterfactual Matching
Ruqi Bai, Yao Ji, Zeyu Zhou +1
Models that learn spurious correlations from training data often fail when deployed in new environments. While many methods aim to learn invariant representations to address this,…
Counterfactual Fairness by Combining Factual and Counterfactual Predictions
Zeyu Zhou, Tianci Liu, Ruqi Bai +3
In high-stake domains such as healthcare and hiring, the role of machine learning (ML) in decision-making raises significant fairness concerns. This work focuses on Counterfactual…
Decoupled Vertical Federated Learning for Practical Training on Vertically Partitioned Data
Avi Amalanshu, Yash Sirvi, David I. Inouye
Vertical Federated Learning (VFL) is an emergent distributed machine learning paradigm for collaborative learning between clients who have disjoint features of common entities. How…
Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions
Mai Elkady, Thu Bui, Bruno Ribeiro +1
There has been a growing excitement that implicit graph generative models could be used to design or discover new molecules for medicine or material design. Because these molecules…