Winnie Xu

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 19

Top Topics

Distributed Representations

Top Venues

Publications

Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff, Dan Jurafsky, Douwe Kiela
KTO: Model Alignment as Prospect Theoretic Optimization. CoRR (2024)
N. Benjamin Erichson, Soon Hoe Lim, Winnie Xu, Francisco Utrera, Ziang Cao, Michael W. Mahoney
NoisyMix: Boosting Model Robustness to Common Corruptions. AISTATS (2024)
Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J. Zico Kolter, Chelsea Finn
Neural Functional Transformers. NeurIPS (2023)
Linqi Zhou, Michael Poli, Winnie Xu, Stefano Massaroli, Stefano Ermon
Deep Latent State Space Models for Time-Series Generation. ICML (2023)
Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J. Zico Kolter, Chelsea Finn
Neural Functional Transformers. CoRR (2023)
Michael Poli, Winnie Xu, Stefano Massaroli, Chenlin Meng, Kuno Kim, Stefano Ermon
Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations. CoRR (2022)
Winnie Xu, Ricky T. Q. Chen, Xuechen Li, David Duvenaud
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations. AISTATS (2022)
Soon Hoe Lim, N. Benjamin Erichson, Francisco Utrera, Winnie Xu, Michael W. Mahoney
Noisy Feature Mixup. ICLR (2022)
Linqi Zhou, Michael Poli, Winnie Xu, Stefano Massaroli, Stefano Ermon
Deep Latent State Space Models for Time-Series Generation. CoRR (2022)
Sören Mindermann, Jan Markus Brauner, Muhammed Razzak, Mrinank Sharma, Andreas Kirsch, Winnie Xu, Benedikt Höltgen, Aidan N. Gomez, Adrien Morisot, Sebastian Farquhar, Yarin Gal
Prioritized Training on Points that are Learnable, Worth Learning, and not yet Learnt. ICML (2022)
Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Sergio Guadarrama, Ian Fischer, Winnie Xu, Eric Jang, Henryk Michalewski, Igor Mordatch
Multi-Game Decision Transformers. NeurIPS (2022)
David Dohan, Winnie Xu, Aitor Lewkowycz, Jacob Austin, David Bieber, Raphael Gontijo Lopes, Yuhuai Wu, Henryk Michalewski, Rif A. Saurous, Jascha Sohl-Dickstein, Kevin Murphy, Charles Sutton
Language Model Cascades. CoRR (2022)
Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Winnie Xu, Sergio Guadarrama, Ian Fischer, Eric Jang, Henryk Michalewski, Igor Mordatch
Multi-Game Decision Transformers. CoRR (2022)
Sören Mindermann, Jan Markus Brauner, Muhammed Razzak, Mrinank Sharma, Andreas Kirsch, Winnie Xu, Benedikt Höltgen, Aidan N. Gomez, Adrien Morisot, Sebastian Farquhar, Yarin Gal
Prioritized Training on Points that are Learnable, Worth Learning, and Not Yet Learnt. CoRR (2022)
N. Benjamin Erichson, Soon Hoe Lim, Francisco Utrera, Winnie Xu, Ziang Cao, Michael W. Mahoney
NoisyMix: Boosting Robustness by Combining Data Augmentations, Stability Training, and Noise Injections. CoRR (2022)
Michael Poli, Winnie Xu, Stefano Massaroli, Chenlin Meng, Kuno Kim, Stefano Ermon
Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations. NeurIPS (2022)
Soon Hoe Lim, N. Benjamin Erichson, Francisco Utrera, Winnie Xu, Michael W. Mahoney
Noisy Feature Mixup. CoRR (2021)
Winnie Xu, Ricky T. Q. Chen, Xuechen Li, David Duvenaud
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations. CoRR (2021)
Sören Mindermann, Muhammed Razzak, Winnie Xu, Andreas Kirsch, Mrinank Sharma, Adrien Morisot, Aidan N. Gomez, Sebastian Farquhar, Jan Markus Brauner, Yarin Gal
Prioritized training on points that are learnable, worth learning, and not yet learned. CoRR (2021)