Ni, Renkun

10 publications

NeurIPS 2023 Battle of the Backbones: A Large-Scale Comparison of Pretrained Models Across Computer Vision Tasks Micah Goldblum, Hossein Souri, Renkun Ni, Manli Shu, Viraj Prabhu, Gowthami Somepalli, Prithvijit Chattopadhyay, Mark Ibrahim, Adrien Bardes, Judy Hoffman, Rama Chellappa, Andrew G Wilson, Tom Goldstein

ICML 2023 GOAT: A Global Transformer on Large-Scale Graphs Kezhi Kong, Jiuhai Chen, John Kirchenbauer, Renkun Ni, C. Bayan Bruss, Tom Goldstein

ICLR 2023 Loss Landscapes Are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent Ping-yeh Chiang, Renkun Ni, David Yu Miller, Arpit Bansal, Jonas Geiping, Micah Goldblum, Tom Goldstein

ICLR 2022 The Close Relationship Between Contrastive Learning and Meta-Learning Renkun Ni, Manli Shu, Hossein Souri, Micah Goldblum, Tom Goldstein

ICML 2021 Data Augmentation for Meta-Learning Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein

NeurIPS 2021 GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training Chen Zhu, Renkun Ni, Zheng Xu, Kezhi Kong, W. Ronny Huang, Tom Goldstein

ICLR 2021 WrapNet: Neural Net Inference with Ultra-Low-Precision Arithmetic Renkun Ni, Hong-min Chu, Oscar Castaneda, Ping-yeh Chiang, Christoph Studer, Tom Goldstein

ICLR 2020 Certified Defenses for Adversarial Patches Ping-Yeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studor, Tom Goldstein

ICML 2020 Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein

AISTATS 2016 Optimal Statistical and Computational Rates for One Bit Matrix Completion Renkun Ni, Quanquan Gu