SueYeon Chung

According to our database, SueYeon Chung authored at least 28 papers between 2015 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Feature Learning beyond the Lazy-Rich Dichotomy: Insights from Representational Geometry.

Chi-Ning Chou, Hang Le, Yichen Wang, SueYeon Chung

CoRR, March, 2025

Spectral Analysis of Representational Similarity with Limited Neurons.

Hyunmo Kang, Abdulkadir Canatar, SueYeon Chung

CoRR, February, 2025

The Geometry of Prompting: Unveiling Distinct Mechanisms of Task Adaptation in Language Models.

Artem Kirsanov, Chi-Ning Chou, Kyunghyun Cho, SueYeon Chung

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

Estimating the Spectral Moments of the Kernel Integral Operator from Finite Sample Matrices.

Chanwoo Chun, SueYeon Chung, Daniel D. Lee

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations.

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

CoRR, 2024

Nonlinear classification of neural manifolds with contextual information.

Francesca Mignacco, Chi-Ning Chou, SueYeon Chung

CoRR, 2024

Neural Population Geometry and Optimal Coding of Tasks with Shared Latent Structure.

Albert J. Wakhloo, Will Slatton, SueYeon Chung

CoRR, 2024

Contrastive-Equivariant Self-Supervised Learning Improves Alignment with Primate Visual Area IT.

Thomas E. Yerxa, Jenelle Feather, Eero P. Simoncelli, SueYeon Chung

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds.

Michael Kuoch, Chi-Ning Chou, Nikhil Parthasarathy, Joel Dapello, James J. DiCarlo, Haim Sompolinsky, SueYeon Chung

Proceedings of the Conference on Parsimony and Learning, 2024

2023

Unsupervised learning on spontaneous retinal activity leads to efficient neural representation geometry.

Andrew Ligeralde, Yilun Kuang, Thomas Edward Yerxa, Miah N. Pitcher, Marla Feller, SueYeon Chung

Proceedings of UniReps: the First Workshop on Unifying Representations in Neural Models, 2023

Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations.

Thomas E. Yerxa, Yilun Kuang, Eero P. Simoncelli, SueYeon Chung

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Spectral Theory of Neural Prediction and Alignment.

Abdulkadir Canatar, Jenelle Feather, Albert J. Wakhloo, SueYeon Chung

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Linear Classification of Neural Manifolds with Correlated Variability.

Albert J. Wakhloo, Tamara J. Sussman, SueYeon Chung

CoRR, 2022

The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks.

Samuel Lippl, L. F. Abbott, SueYeon Chung

CoRR, 2022

Divisive Feature Normalization Improves Image Recognition Performance in AlexNet.

Michelle Miller, SueYeon Chung, Kenneth D. Miller

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks.

Landan Seguin, Anthony Ndirango, Neeli Mishra, SueYeon Chung, Tyler Lee

CoRR, 2021

Statistical Mechanics of Neural Processing of Object Manifolds.

SueYeon Chung

CoRR, 2021

Neural population geometry: An approach for understanding biological and artificial neural networks.

SueYeon Chung, L. F. Abbott

CoRR, 2021

Syntactic Perturbations Reveal Representational Correlates of Hierarchical Phrase Structure in Pretrained Language Models.

Matteo Alleman, Jonathan Mamou, Miguel A. Del Rio, Hanlin Tang, Yoon Kim, SueYeon Chung

Proceedings of the 6th Workshop on Representation Learning for NLP, 2021

Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception.

Joel Dapello, Jenelle Feather, Hang Le, Tiago Marques, David D. Cox, Josh H. McDermott, James J. DiCarlo, SueYeon Chung

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Credit Assignment Through Broadcasting a Global Error Vector.

David G. Clark, L. F. Abbott, SueYeon Chung

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the geometry of generalization and memorization in deep neural networks.

Cory Stephenson, Suchismita Padhy, Abhinav Ganesh, Yue Hui, Hanlin Tang, SueYeon Chung

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

On 1/n neural representation and robustness.

Josue Nassar, Piotr A. Sokól, SueYeon Chung, Kenneth D. Harris, Il Memming Park

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Emergence of Separable Manifolds in Deep Language Representations.

Jonathan Mamou, Hang Le, Miguel Del Rio, Cory Stephenson, Hanlin Tang, Yoon Kim, SueYeon Chung

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Untangling in Invariant Speech Recognition.

Cory Stephenson, Jenelle Feather, Suchismita Padhy, Oguz H. Elibol, Hanlin Tang, Josh H. McDermott, SueYeon Chung

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Learning Data Manifolds with a Cutting Plane Method.

SueYeon Chung, Uri Cohen, Haim Sompolinsky, Daniel D. Lee

Neural Comput., 2018

2017

Classification and Geometry of General Perceptual Manifolds.

SueYeon Chung, Daniel D. Lee, Haim Sompolinsky

CoRR, 2017

2015

Classification of Manifolds by Single-Layer Neural Networks.

SueYeon Chung, Daniel D. Lee, Haim Sompolinsky

CoRR, 2015