PACm-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime. - Warren R. Morningstar; Alexander A. Alemi; Joshua V. Dillon (CoRR, 2020)

VIB is Half Bayes. - Alexander A. Alemi; Warren R. Morningstar; Ben Poole; Ian Fischer; Joshua V. Dillon (CoRR, 2020)

Density of States Estimation for Out of Distribution Detection. - Warren R. Morningstar; Cusuh Ham; Andrew G. Gallagher; Balaji Lakshminarayanan; Alexander A. Alemi; Joshua V. Dillon (AISTATS, 2021)

Automatic Differentiation Variational Inference with Mixtures. - Warren R. Morningstar; Sharad M. Vikram; Cusuh Ham; Andrew G. Gallagher; Joshua V. Dillon (AISTATS, 2021)

PACm-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime. - Warren R. Morningstar; Alex Alemi; Joshua V. Dillon (AISTATS, 2022)

What Do We Mean by Generalization in Federated Learning? - Honglin Yuan 002; Warren Richard Morningstar; Lin Ning 001; Karan Singhal (ICLR, 2022)

Federated Training of Dual Encoding Models on Small Non-IID Client Datasets. - Raviteja Vemulapalli; Warren Richard Morningstar; Philip Andrew Mansfield; Hubert Eichner; Karan Singhal; Arash Afkanpour; Bradley Green (CoRR, 2022)

Weighted Ensemble Self-Supervised Learning. - Yangjun Ruan; Saurabh Singh; Warren Richard Morningstar; Alexander A. Alemi; Sergey Ioffe; Ian Fischer; Joshua V. Dillon (ICLR, 2023)

Random field augmentations for self-supervised representation learning. - Philip Andrew Mansfield; Arash Afkanpour; Warren Richard Morningstar; Karan Singhal (NeurReps, 2023)

Towards Federated Learning Under Resource Constraints via Layer-wise Training and Depth Dropout. - Pengfei Guo; Warren Richard Morningstar; Raviteja Vemulapalli; Karan Singhal; Vishal M. Patel; Philip Andrew Mansfield (CoRR, 2023)

Augmentations vs Algorithms: What Works in Self-Supervised Learning. - Warren R. Morningstar; Alex Bijamov; Chris Duvarney; Luke Friedman; Neha Mukund Kalibhat; Luyang Liu; Philip Andrew Mansfield; Renan A. Rojas-Gomez; Karan Singhal; Bradley Green; Sushant Prakash (CoRR, 2024)

SASSL: Enhancing Self-Supervised Learning via Neural Style Transfer. - Renan A. Rojas-Gomez; Karan Singhal; Ali Etemad; Alex Bijamov; Warren Richard Morningstar; Philip Andrew Mansfield (Trans. Mach. Learn. Res., 2024)

Federated Variational Inference: Towards Improved Personalization and Generalization. - Elahe Vedadi; Joshua V. Dillon; Philip Andrew Mansfield; Karan Singhal; Arash Afkanpour; Warren Richard Morningstar (Trans. Mach. Learn. Res., 2024)

Forte : Finding Outliers with Representation Typicality Estimation. - Debargha Ganguly; Warren Richard Morningstar; Andrew Seohwan Yu; Vipin Chaudhary (ICLR, 2025)

Disentangling the Effects of Data Augmentation and Format Transform in Self-Supervised Learning of Image Representations. - Neha Mukund Kalibhat; Warren Richard Morningstar; Alex Bijamov; Luyang Liu; Karan Singhal; Philip Andrew Mansfield (UniReps, 2025)