Morningstar, Warren Richard

8 publications

ICLR 2026 Trust the Typical Debargha Ganguly, Sreehari Sankar, Biyao Zhang, Vikash Singh, Kanan Gupta, Harshini Kavuru, Alan Luo, Weicong Chen, Warren Richard Morningstar, Raghu Machiraju, Vipin Chaudhary

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

NeurIPSW 2024 Disentangling the Effects of Data Augmentation and Format Transform in Self-Supervised Learning of Image Representations Neha Kalibhat, Warren Richard Morningstar, Alex Bijamov, Luyang Liu, Karan Singhal, Philip Andrew Mansfield

TMLR 2024 Federated Variational Inference: Towards Improved Personalization and Generalization Elahe Vedadi, Joshua V. Dillon, Philip Andrew Mansfield, Karan Singhal, Arash Afkanpour, Warren Richard Morningstar

TMLR 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

ICLRW 2023 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

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

ICLR 2022 What Do We Mean by Generalization in Federated Learning? Honglin Yuan, Warren Richard Morningstar, Lin Ning, Karan Singhal