SueYeon Chung

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 32

Top Topics

Cutting Plane Method

Unsupervised Learning

Linear Classification

Top Venues

Publications

Francesca Mignacco, Chi-Ning Chou, SueYeon Chung
Nonlinear classification of neural manifolds with contextual information. CoRR (2024)
Albert J. Wakhloo, Will Slatton, SueYeon Chung
Neural Population Geometry and Optimal Coding of Tasks with Shared Latent Structure. CoRR (2024)
Rylan Schaeffer, Victor Lecomte, Dhruv Bhandarkar Pai, Andres Carranza, Berivan Isik, Alyssa Unell, Mikail Khona, Thomas E. Yerxa, Yann LeCun, SueYeon Chung, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo
Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations. CoRR (2024)
Michael Kuoch, Chi-Ning Chou, Nikhil Parthasarathy, Joel Dapello, James J. DiCarlo, Haim Sompolinsky, SueYeon Chung
Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds. CoRR (2023)
Abdulkadir Canatar, Jenelle Feather, Albert J. Wakhloo, SueYeon Chung
A Spectral Theory of Neural Prediction and Alignment. CoRR (2023)
Abdulkadir Canatar, Jenelle Feather, Albert J. Wakhloo, SueYeon Chung
A Spectral Theory of Neural Prediction and Alignment. NeurIPS (2023)
Andrew Ligeralde, Yilun Kuang, Thomas Edward Yerxa, Miah N. Pitcher, Marla Feller, SueYeon Chung
Unsupervised learning on spontaneous retinal activity leads to efficient neural representation geometry. UniReps (2023)
Thomas E. Yerxa, Yilun Kuang, Eero P. Simoncelli, SueYeon Chung
Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations. CoRR (2023)
Thomas E. Yerxa, Yilun Kuang, Eero P. Simoncelli, SueYeon Chung
Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations. NeurIPS (2023)
Michelle Miller, SueYeon Chung, Kenneth D. Miller
Divisive Feature Normalization Improves Image Recognition Performance in AlexNet. ICLR (2022)
Albert J. Wakhloo, Tamara J. Sussman, SueYeon Chung
Linear Classification of Neural Manifolds with Correlated Variability. CoRR (2022)
Samuel Lippl, L. F. Abbott, SueYeon Chung
The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks. CoRR (2022)
Cory Stephenson, Suchismita Padhy, Abhinav Ganesh, Yue Hui, Hanlin Tang, SueYeon Chung
On the geometry of generalization and memorization in deep neural networks. CoRR (2021)
David G. Clark, L. F. Abbott, SueYeon Chung
Credit Assignment Through Broadcasting a Global Error Vector. CoRR (2021)
SueYeon Chung, L. F. Abbott
Neural population geometry: An approach for understanding biological and artificial neural networks. CoRR (2021)
SueYeon Chung
Statistical Mechanics of Neural Processing of Object Manifolds. CoRR (2021)
Matteo Alleman, Jonathan Mamou, Miguel A. Del Rio, Hanlin Tang, Yoon Kim, SueYeon Chung
Syntactic Perturbations Reveal Representational Correlates of Hierarchical Phrase Structure in Pretrained Language Models. CoRR (2021)
Landan Seguin, Anthony Ndirango, Neeli Mishra, SueYeon Chung, Tyler Lee
Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks. CoRR (2021)
David G. Clark, L. F. Abbott, SueYeon Chung
Credit Assignment Through Broadcasting a Global Error Vector. NeurIPS (2021)
Joel Dapello, Jenelle Feather, Hang Le, Tiago Marques, David D. Cox, Josh H. McDermott, James J. DiCarlo, SueYeon Chung
Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception. NeurIPS (2021)
Cory Stephenson, Suchismita Padhy, Abhinav Ganesh, Yue Hui, Hanlin Tang, SueYeon Chung
On the geometry of generalization and memorization in deep neural networks. ICLR (2021)
Joel Dapello, Jenelle Feather, Hang Le, Tiago Marques, David D. Cox, Josh H. McDermott, James J. DiCarlo, SueYeon Chung
Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception. CoRR (2021)
Matteo Alleman, Jonathan Mamou, Miguel A. Del Rio, Hanlin Tang, Yoon Kim, SueYeon Chung
Syntactic Perturbations Reveal Representational Correlates of Hierarchical Phrase Structure in Pretrained Language Models. RepL4NLP@ACL-IJCNLP (2021)
Jonathan Mamou, Hang Le, Miguel Del Rio, Cory Stephenson, Hanlin Tang, Yoon Kim, SueYeon Chung
Emergence of Separable Manifolds in Deep Language Representations. ICML (2020)
Jonathan Mamou, Hang Le, Miguel Del Rio, Cory Stephenson, Hanlin Tang, Yoon Kim, SueYeon Chung
Emergence of Separable Manifolds in Deep Language Representations. CoRR (2020)
Josue Nassar, Piotr A. Sokól, SueYeon Chung, Kenneth D. Harris, Il Memming Park
On 1/n neural representation and robustness. NeurIPS (2020)
Josue Nassar, Piotr Aleksander Sokól, SueYeon Chung, Kenneth D. Harris, Il Memming Park
On 1/n neural representation and robustness. CoRR (2020)
Cory Stephenson, Jenelle Feather, Suchismita Padhy, Oguz H. Elibol, Hanlin Tang, Josh McDermott, SueYeon Chung
Untangling in Invariant Speech Recognition. CoRR (2020)
Cory Stephenson, Jenelle Feather, Suchismita Padhy, Oguz H. Elibol, Hanlin Tang, Josh McDermott, SueYeon Chung
Untangling in Invariant Speech Recognition. NeurIPS (2019)
SueYeon Chung, Uri Cohen, Haim Sompolinsky, Daniel D. Lee
Learning Data Manifolds with a Cutting Plane Method. Neural Comput. 30 (10) (2018)
SueYeon Chung, Uri Cohen, Haim Sompolinsky, Daniel D. Lee
Learning Data Manifolds with a Cutting Plane Method. CoRR (2017)
SueYeon Chung, Daniel D. Lee, Haim Sompolinsky
Classification and Geometry of General Perceptual Manifolds. CoRR (2017)
SueYeon Chung, Daniel D. Lee, Haim Sompolinsky
Classification of Manifolds by Single-Layer Neural Networks. CoRR (2015)