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Workshop
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Fri 10:51
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"Bias and Generalization of Deep Generative Models" by Stefano Ermon, Stanford University
Stefano Ermon
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Poster
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Tue 9:00
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Physics-aware, probabilistic model order reduction with guaranteed stability
Sebastian Kaltenbach · PS Koutsourelakis
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Poster
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Tue 1:00
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What they do when in doubt: a study of inductive biases in seq2seq learners
Kharitonov Eugene · Rahma Chaabouni
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Poster
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Mon 9:00
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Learning from others' mistakes: Avoiding dataset biases without modeling them
Victor Sanh · Thomas Wolf · Yonatan Belinkov · Alexander M Rush
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Poster
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Thu 9:00
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Noise or Signal: The Role of Image Backgrounds in Object Recognition
Kai Xiao · Logan Engstrom · Andrew Ilyas · Aleksander Madry
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Poster
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Mon 9:00
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Predicting Inductive Biases of Pre-Trained Models
Charles Lovering · Rohan Jha · Tal Linzen · Ellie Pavlick
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Poster
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Thu 9:00
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Rethinking Soft Labels for Knowledge Distillation: A Bias–Variance Tradeoff Perspective
Helong Zhou · Liangchen Song · Jiajie Chen · Ye Zhou · Guoli Wang · Junsong Yuan · Qian Zhang
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Poster
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Tue 1:00
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A Distributional Approach to Controlled Text Generation
Muhammad Khalifa · Hady Elsahar · Marc Dymetman
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Oral
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Mon 4:15
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A Distributional Approach to Controlled Text Generation
Muhammad Khalifa · Hady Elsahar · Marc Dymetman
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Poster
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Thu 9:00
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Variational Information Bottleneck for Effective Low-Resource Fine-Tuning
Rabeeh Karimi Mahabadi · Yonatan Belinkov · James Henderson
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