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Out-of-Distribution Robustness via Targeted Augmentations
Irena Gao · Shiori Sagawa · Pang Wei Koh · Tatsunori Hashimoto · Percy Liang
Thu 14:00 Generative multitask learning mitigates target-causing confounding
Taro Makino · Krzysztof Geras · Kyunghyun Cho
Tue 9:00 Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free
Alexander Meinke · Julian Bitterwolf · Matthias Hein
Your Out-of-Distribution Detection Method is Not Robust!
Mohammad Azizmalayeri · Arshia Soltani Moakhar · Arman Zarei · Reihaneh Zohrabi · Mohammad Manzuri · Mohammad Hossein Rohban
Thu 9:00 Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models
Manli Shu · Weili Nie · De-An Huang · Zhiding Yu · Tom Goldstein · Anima Anandkumar · Chaowei Xiao
Tue 14:00 Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift
Christina Baek · Yiding Jiang · Aditi Raghunathan · J. Zico Kolter
Thu 9:00 Assaying Out-Of-Distribution Generalization in Transfer Learning
Florian Wenzel · Andrea Dittadi · Peter Gehler · Carl-Johann Simon-Gabriel · Max Horn · Dominik Zietlow · David Kernert · Chris Russell · Thomas Brox · Bernt Schiele · Bernhard Schölkopf · Francesco Locatello
Thu 14:00 MEMO: Test Time Robustness via Adaptation and Augmentation
Marvin Zhang · Sergey Levine · Chelsea Finn
Affinity Workshop
Improving Robustness to Distribution Shift with Methods from Differential Privacy
Neha Hulkund
Sat 8:30 Fine-Tuning without Distortion: Improving Robustness to Distribution Shifts
Percy Liang · Ananya Kumar
Distributionally Robust Bayesian Optimization with φ-divergences
Hisham Husain · Vu Nguyen · Anton van den Hengel
Visual response inhibition for increased robustness of convolutional networks to distribution shifts
Nicola Strisciuglio · George Azzopardi