Brian R. Bartoldson

According to our database, Brian R. Bartoldson authored at least 9 papers between 2018 and 2024.

Collaborative distances:

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

2024

Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression.

Junyuan Hong, Jinhao Duan, Chenhui Zhang, Zhangheng Li, Chulin Xie, Kelsey Lieberman, James Diffenderfer, Brian R. Bartoldson, Ajay Jaiswal, Kaidi Xu, Bhavya Kailkhura, Dan Hendrycks, Dawn Song, Zhangyang Wang, Bo Li

CoRR, 2024

2023

Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities.

Brian R. Bartoldson, Bhavya Kailkhura, Davis W. Blalock

J. Mach. Learn. Res., 2023

NEFTune: Noisy Embeddings Improve Instruction Finetuning.

Neel Jain, Ping-yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein

CoRR, 2023

Scientific Computing Algorithms to Learn Enhanced Scalable Surrogates for Mesh Physics.

Brian R. Bartoldson, Yeping Hu, Amar Saini, Jose Cadena, Yucheng Fu, Jie Bao, Zhijie Xu, Brenda Ng, Phan Nguyen

CoRR, 2023

2022

Models Out of Line: A Fourier Lens on Distribution Shift Robustness.

Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer, Bhavya Kailkhura, Timo Bremer

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Latent Space Simulation for Carbon Capture Design Optimization.

Brian R. Bartoldson, Rui Wang, Yucheng Fu, David Widemann, Sam Nguyen, Jie Bao, Zhijie Xu, Brenda Ng

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

A Winning Hand: Compressing Deep Networks Can Improve Out-of-Distribution Robustness.

James Diffenderfer, Brian R. Bartoldson, Shreya Chaganti, Jize Zhang, Bhavya Kailkhura

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

2020

The Generalization-Stability Tradeoff In Neural Network Pruning.

Brian R. Bartoldson, Ari S. Morcos, Adrian Barbu, Gordon Erlebacher

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

2018

Enhancing the Regularization Effect of Weight Pruning in Artificial Neural Networks.

Brian R. Bartoldson, Adrian Barbu, Gordon Erlebacher

CoRR, 2018