Yiding Jiang

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 32

Top Topics

Monitoring System

Image Generation

Reinforcement Learning

Wavelet Decomposition

Top Venues

Publications

Yiding Jiang, Christina Baek, J. Zico Kolter
On the Joint Interaction of Models, Data, and Features. ICLR (2024)
Yutong He, Alexander Robey, Naoki Murata, Yiding Jiang, Joshua Williams, George J. Pappas, Hamed Hassani, Yuki Mitsufuji, Ruslan Salakhutdinov, J. Zico Kolter
Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation. CoRR (2024)
Victor Akinwande, Yiding Jiang, Dylan Sam, J. Zico Kolter
Understanding prompt engineering may not require rethinking generalization. ICLR (2024)
Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J. Zico Kolter, Chelsea Finn
Neural Functional Transformers. NeurIPS (2023)
Yiding Jiang, J. Zico Kolter, Roberta Raileanu
On the Importance of Exploration for Generalization in Reinforcement Learning. CoRR (2023)
Allan Zhou, Kaien Yang, Kaylee Burns, Yiding Jiang, Samuel Sokota, J. Zico Kolter, Chelsea Finn
Permutation Equivariant Neural Functionals. CoRR (2023)
Yiding Jiang, J. Zico Kolter, Roberta Raileanu
On the Importance of Exploration for Generalization in Reinforcement Learning. NeurIPS (2023)
Xianchen Wang, Di Cao, Yiding Jiang, Yanjing Lei, Linghao Ying
A Wavelet Decomposition Network Based Edge Monitoring System for Classification of Electrical Equipment. SMC (2023)
Victor Akinwande, Yiding Jiang, Dylan Sam, J. Zico Kolter
Understanding prompt engineering may not require rethinking generalization. CoRR (2023)
Hariharan Manikandan, Yiding Jiang, J. Zico Kolter
Language Models are Weak Learners. NeurIPS (2023)
Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J. Zico Kolter, Chelsea Finn
Neural Functional Transformers. CoRR (2023)
Yiding Jiang, Christina Baek, J. Zico Kolter
On the Joint Interaction of Models, Data, and Features. CoRR (2023)
Allan Zhou, Kaien Yang, Kaylee Burns, Adriano Cardace, Yiding Jiang, Samuel Sokota, J. Zico Kolter, Chelsea Finn
Permutation Equivariant Neural Functionals. NeurIPS (2023)
Hariharan Manikandan, Yiding Jiang, J. Zico Kolter
Language models are weak learners. CoRR (2023)
Christina Baek, Yiding Jiang, Aditi Raghunathan, Zico Kolter
Agreement-on-the-Line: Predicting the Performance of Neural Networks under Distribution Shift. CoRR (2022)
Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter
Assessing Generalization of SGD via Disagreement. ICLR (2022)
Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, Zico Kolter, Chelsea Finn
Learning Options via Compression. CoRR (2022)
Christina Baek, Yiding Jiang, Aditi Raghunathan, J. Zico Kolter
Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift. NeurIPS (2022)
Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn
Learning Options via Compression. NeurIPS (2022)
Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter
Assessing Generalization of SGD via Disagreement. CoRR (2021)
Jivat Neet Kaur, Yiding Jiang, Paul Pu Liang
Ask & Explore: Grounded Question Answering for Curiosity-Driven Exploration. CoRR (2021)
Yiding Jiang, Parth Natekar, Manik Sharma, Sumukh K. Aithal, Dhruva Kashyap, Natarajan Subramanyam, Carlos Lassance, Daniel M. Roy, Gintare Karolina Dziugaite, Suriya Gunasekar, Isabelle Guyon, Pierre Foret, Scott Yak, Hossein Mobahi, Behnam Neyshabur, Samy Bengio
Methods and Analysis of The First Competition in Predicting Generalization of Deep Learning. NeurIPS (Competition and Demos) (2020)
Yiding Jiang, Behnam Neyshabur, Hossein Mobahi, Dilip Krishnan, Samy Bengio
Fantastic Generalization Measures and Where to Find Them. ICLR (2020)
Yiding Jiang, Pierre Foret, Scott Yak, Daniel M. Roy, Hossein Mobahi, Gintare Karolina Dziugaite, Samy Bengio, Suriya Gunasekar, Isabelle Guyon, Behnam Neyshabur
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning. CoRR (2020)
Xingyou Song, Yiding Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur
Observational Overfitting in Reinforcement Learning. ICLR (2020)
David Wang, David Tseng, Pusong Li, Yiding Jiang, Menglong Guo, Michael Danielczuk, Jeffrey Mahler, Jeffrey Ichnowski, Ken Goldberg
Adversarial Grasp Objects. CASE (2019)
Yiding Jiang, Dilip Krishnan, Hossein Mobahi, Samy Bengio
Predicting the Generalization Gap in Deep Networks with Margin Distributions. ICLR (Poster) (2019)
Yiding Jiang, Behnam Neyshabur, Hossein Mobahi, Dilip Krishnan, Samy Bengio
Fantastic Generalization Measures and Where to Find Them. CoRR (2019)
Xingyou Song, Yiding Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur
Observational Overfitting in Reinforcement Learning. CoRR (2019)
Yiding Jiang, Shixiang Gu, Kevin Murphy, Chelsea Finn
Language as an Abstraction for Hierarchical Deep Reinforcement Learning. NeurIPS (2019)
Yiding Jiang, Shixiang Gu, Kevin Murphy, Chelsea Finn
Language as an Abstraction for Hierarchical Deep Reinforcement Learning. CoRR (2019)
Yiding Jiang, Dilip Krishnan, Hossein Mobahi, Samy Bengio
Predicting the Generalization Gap in Deep Networks with Margin Distributions. CoRR (2018)