Multi-prize lottery ticket hypothesis: Finding accurate binary neural networks by pruning a randomly weighted network J Diffenderfer, B Kailkhura arXiv preprint arXiv:2103.09377, 2021 | 81 | 2021 |
Error analysis of zfp compression for floating-point data J Diffenderfer, AL Fox, JA Hittinger, G Sanders, PG Lindstrom SIAM Journal on Scientific Computing 41 (3), A1867-A1898, 2019 | 75 | 2019 |
A winning hand: Compressing deep networks can improve out-of-distribution robustness J Diffenderfer, B Bartoldson, S Chaganti, J Zhang, B Kailkhura Advances in neural information processing systems 34, 664-676, 2021 | 57 | 2021 |
Stability analysis of inline ZFP compression for floating-point data in iterative methods A Fox, J Diffenderfer, J Hittinger, G Sanders, P Lindstrom SIAM Journal on Scientific Computing 42 (5), A2701-A2730, 2020 | 20 | 2020 |
HPAC: evaluating approximate computing techniques on HPC OpenMP applications K Parasyris, G Georgakoudis, H Menon, J Diffenderfer, I Laguna, ... Proceedings of the International Conference for High Performance Computing …, 2021 | 11 | 2021 |
Gtbench: Uncovering the strategic reasoning limitations of llms via game-theoretic evaluations J Duan, R Zhang, J Diffenderfer, B Kailkhura, L Sun, E Stengel-Eskin, ... arXiv preprint arXiv:2402.12348, 2024 | 6 | 2024 |
QDOT: Quantized dot product kernel for approximate high-performance computing J Diffenderfer, D Osei-Kuffuor, H Menon arXiv preprint arXiv:2105.00115, 2021 | 5 | 2021 |
Variable precision computing JA Hittinger, PG Lindstrom, H Bhatia, PT Bremer, DM Copeland, ... Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2019 | 5 | 2019 |
Deepzero: Scaling up zeroth-order optimization for deep model training A Chen, Y Zhang, J Jia, J Diffenderfer, J Liu, K Parasyris, Y Zhang, ... arXiv preprint arXiv:2310.02025, 2023 | 3 | 2023 |
Zeroth-order sciml: Non-intrusive integration of scientific software with deep learning I Tsaknakis, B Kailkhura, S Liu, D Loveland, J Diffenderfer, AM Hiszpanski, ... arXiv preprint arXiv:2206.02785, 2022 | 3 | 2022 |
A bijection between two classes of restricted compositions J Diffenderfer Fibonacci Quart 50 (4), 360-365, 2012 | 3 | 2012 |
Algorithm 1035: a gradient-based implementation of the polyhedral active set algorithm WW Hager, H Zhang ACM Transactions on Mathematical Software 49 (2), 1-13, 2023 | 2 | 2023 |
Approximate High-Performance Computing: A Fast and Energy-Efficient Computing Paradigm in the Post-Moore Era H Menon, J Diffenderfer, G Georgakoudis, I Laguna, MO Lam, ... IT Professional 25 (2), 7-15, 2023 | 2 | 2023 |
Approximate computing through the lens of uncertainty quantification K Parasyris, J Diffenderfer, H Menon, I Laguna, J Vanover, R Vogt, ... SC22: International Conference for High Performance Computing, Networking …, 2022 | 2 | 2022 |
Benchmarking test-time unsupervised deep neural network adaptation on edge devices K Bhardwaj, J Diffenderfer, B Kailkhura, M Gokhale 2022 IEEE International Symposium on Performance Analysis of Systems and …, 2022 | 2 | 2022 |
Neural Image Compression: Generalization, Robustness, and Spectral Biases K Lieberman, J Diffenderfer, C Godfrey, B Kailkhura ICML 2023 Workshop Neural Compression: From Information Theory to Applications, 2023 | 1 | 2023 |
Unsupervised test-time adaptation of deep neural networks at the edge: a case study K Bhardwaj, J Diffenderfer, B Kailkhura, M Gokhale 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), 412-417, 2022 | 1 | 2022 |
A framework for error-bounded approximate computing, with an application to dot products J Diffenderfer, D Osei-Kuffuor, H Menon SIAM Journal on Scientific Computing 44 (3), A1290-A1314, 2022 | 1 | 2022 |
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning J Jia, Y Zhang, Y Zhang, J Liu, B Runwal, J Diffenderfer, B Kailkhura, ... arXiv preprint arXiv:2404.18239, 2024 | | 2024 |
End-to-End Mesh Optimization of a Hybrid Deep Learning Black-Box PDE Solver S Ma, J Diffenderfer, B Kailkhura, Y Zhou arXiv preprint arXiv:2404.11766, 2024 | | 2024 |