A Volume Integral Equation Stokes Solver for Problems with Variable Coefficients. - Dhairya Malhotra; Amir Gholami; George Biros (SC, 2014)

FFT, FMM, or MULTIGRID? A comparative study of state-of-the-art poisson solvers. - Amir Gholami; Dhairya Malhotra; Hari Sundar; George Biros (CoRR, 2014)

AccFFT: A library for distributed-memory FFT on CPU and GPU architectures. - Amir Gholami; Judith Hill; Dhairya Malhotra; George Biros (CoRR, 2015)

Distributed-memory large deformation diffeomorphic 3D image registration. - Andreas Mang; Amir Gholami; George Biros (SC, 2016)

FFT, FMM, or Multigrid? A comparative Study of State-Of-the-Art Poisson Solvers for Uniform and Nonuniform Grids in the Unit Cube. - Amir Gholami; Dhairya Malhotra; Hari Sundar; George Biros (SIAM J. Sci. Comput., 2016)

A framework for scalable biophysics-based image analysis. - Amir Gholami; Andreas Mang; Klaudius Scheufele; Christos Davatzikos; Miriam Mehl; George Biros (SC, 2017)

Integrated Model and Data Parallelism in Training Neural Networks. - Amir Gholami; Ariful Azad; Kurt Keutzer; Aydin Buluç (CoRR, 2017)

SqueezeNext: Hardware-Aware Neural Network Design. - Amir Gholami; Kiseok Kwon; Bichen Wu; Zizheng Tai; Xiangyu Yue 001; Peter H. Jin; Sicheng Zhao; Kurt Keutzer (CVPR Workshops, 2018)

Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions. - Bichen Wu; Alvin Wan; Xiangyu Yue 001; Peter H. Jin; Sicheng Zhao; Noah Golmant; Amir Gholaminejad; Joseph Gonzalez 001; Kurt Keutzer (CVPR, 2018)

A Novel Domain Adaptation Framework for Medical Image Segmentation. - Amir Gholami; Shashank Subramanian; Varun Shenoy; Naveen Himthani; Xiangyu Yue 001; Sicheng Zhao; Peter H. Jin; George Biros; Kurt Keutzer (BrainLes@MICCAI (2), 2018)

Hessian-based Analysis of Large Batch Training and Robustness to Adversaries. - Zhewei Yao; Amir Gholami; Qi Lei; Kurt Keutzer; Michael W. Mahoney (NeurIPS, 2018)

Integrated Model, Batch, and Domain Parallelism in Training Neural Networks. - Amir Gholami; Ariful Azad; Peter H. Jin; Kurt Keutzer; Aydin Buluç (SPAA, 2018)

PDE-constrained optimization in medical image analysis. - Andreas Mang; Amir Gholami; Christos Davatzikos; George Biros (CoRR, 2018)

Large batch size training of neural networks with adversarial training and second-order information. - Zhewei Yao; Amir Gholami; Kurt Keutzer; Michael W. Mahoney (CoRR, 2018)

On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent. - Noah Golmant; Nikita Vemuri; Zhewei Yao; Vladimir Feinberg; Amir Gholami; Kai Rothauge; Michael W. Mahoney; Joseph Gonzalez 001 (CoRR, 2018)

Parameter Re-Initialization through Cyclical Batch Size Schedules. - Norman Mu; Zhewei Yao; Amir Gholami; Kurt Keutzer; Michael W. Mahoney (CoRR, 2018)

Trust Region Based Adversarial Attack on Neural Networks. - Zhewei Yao; Amir Gholami; Peng Xu; Kurt Keutzer; Michael W. Mahoney (CVPR, 2019)

HAWQ: Hessian AWare Quantization of Neural Networks With Mixed-Precision. - Zhen Dong 003; Zhewei Yao; Amir Gholami; Michael W. Mahoney; Kurt Keutzer (ICCV, 2019)

ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs. - Amir Gholaminejad; Kurt Keutzer; George Biros (IJCAI, 2019)

ANODEV2: A Coupled Neural ODE Framework. - Tianjun Zhang; Zhewei Yao; Amir Gholami; Joseph E. Gonzalez; Kurt Keutzer; Michael W. Mahoney; George Biros (NeurIPS, 2019)

A Simulation Platform Design and Kinematics Analysis of MRL-HSL Humanoid Robot. - Amir Gholami; Milad Moradi; Majid Majidi (RoboCup, 2019)

MRL Champion Team Paper in Humanoid TeenSize League of RoboCup 2019. - Hamed Mahmudi; Amir Gholami; Mohammad Hossein Delavaran; Soheil Khatibi; Saeid Bazargan; Milad Moradi; Bita Alaee; Arash Rahmani; Kazem Firouzmandi Bandpey; Peyman Fallahzadeh; Meisam Teimouri (RoboCup, 2019)

ANODEV2: A Coupled Neural ODE Evolution Framework. - Tianjun Zhang; Zhewei Yao; Amir Gholami; Kurt Keutzer; Joseph Gonzalez 001; George Biros; Michael W. Mahoney (CoRR, 2019)

HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks. - Zhen Dong 003; Zhewei Yao; Yaohui Cai; Daiyaan Arfeen; Amir Gholami; Michael W. Mahoney; Kurt Keutzer (CoRR, 2019)

Co-design of deep neural nets and neural net accelerators for embedded vision applications. - Alon Amid; Kiseok Kwon; Amir Gholami; Bichen Wu; Krste Asanovic; Kurt Keutzer (IBM J. Res. Dev., 2019)

A novel LMI-based robust model predictive control for DFIG-based wind energy conversion systems. - Amir Gholami; Alireza Sahab; Abdolreza Tavakoli; Behnam Alizadeh (Kybernetika, 2019)

CLAIRE: A Distributed-Memory Solver for Constrained Large Deformation Diffeomorphic Image Registration. - Andreas Mang; Amir Gholami; Christos Davatzikos; George Biros (SIAM J. Sci. Comput., 2019)

Personalized Emotion Recognition by Personality-Aware High-Order Learning of Physiological Signals. - Sicheng Zhao; Amir Gholaminejad; Guiguang Ding; Yue Gao 002; Jungong Han; Kurt Keutzer (ACM Trans. Multim. Comput. Commun. Appl., 2019)

Inefficiency of K-FAC for Large Batch Size Training. - Linjian Ma; Gabe Montague; Jiayu Ye; Zhewei Yao; Amir Gholami; Kurt Keutzer; Michael W. Mahoney (AAAI, 2020)

Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT. - Sheng Shen 001; Zhen Dong 003; Jiayu Ye; Linjian Ma; Zhewei Yao; Amir Gholami; Michael W. Mahoney; Kurt Keutzer (AAAI, 2020)

PyHessian: Neural Networks Through the Lens of the Hessian. - Zhewei Yao; Amir Gholami; Kurt Keutzer; Michael W. Mahoney (IEEE BigData, 2020)

ZeroQ: A Novel Zero Shot Quantization Framework. - Yaohui Cai; Zhewei Yao; Zhen Dong 003; Amir Gholami; Michael W. Mahoney; Kurt Keutzer (CVPR, 2020)

PowerNorm: Rethinking Batch Normalization in Transformers. - Sheng Shen 001; Zhewei Yao; Amir Gholami; Michael W. Mahoney; Kurt Keutzer (ICML, 2020)

Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization. - Paras Jain 001; Ajay Jain; Aniruddha Nrusimha; Amir Gholami; Pieter Abbeel; Kurt Keutzer; Ion Stoica; Joseph Gonzalez 001 (MLSys, 2020)

HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks. - Zhen Dong 003; Zhewei Yao; Daiyaan Arfeen; Amir Gholami; Michael W. Mahoney; Kurt Keutzer (NeurIPS, 2020)

Boundary thickness and robustness in learning models. - Yaoqing Yang; Rajiv Khanna; Yaodong Yu; Amir Gholami; Kurt Keutzer; Joseph E. Gonzalez; Kannan Ramchandran; Michael W. Mahoney (NeurIPS, 2020)

Rethinking Batch Normalization in Transformers. - Sheng Shen 001; Zhewei Yao; Amir Gholami; Michael W. Mahoney; Kurt Keutzer (CoRR, 2020)

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning. - Zhewei Yao; Amir Gholami; Sheng Shen 001; Kurt Keutzer; Michael W. Mahoney (CoRR, 2020)

HAWQV3: Dyadic Neural Network Quantization. - Zhewei Yao; Zhen Dong 003; Zhangcheng Zheng; Amir Gholami; Jiali Yu; Eric Tan; Leyuan Wang; Qijing Huang 001; Yida Wang; Michael W. Mahoney; Kurt Keutzer (CoRR, 2020)

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning. - Zhewei Yao; Amir Gholami; Sheng Shen 001; Mustafa Mustafa; Kurt Keutzer; Michael W. Mahoney (AAAI, 2021)

Denoising and Bad Data Detection in Distribution Phasor Measurements using Filtering, Clustering and Koopman Mode Analysis. - Amirkhosro Vosughi; Amir Gholami; Anurag K. Srivastava 001 (IAS, 2021)

I-BERT: Integer-only BERT Quantization. - Sehoon Kim 001; Amir Gholami; Zhewei Yao; Michael W. Mahoney; Kurt Keutzer (ICML, 2021)

HAWQ-V3: Dyadic Neural Network Quantization. - Zhewei Yao; Zhen Dong 003; Zhangcheng Zheng; Amir Gholami; Jiali Yu; Eric Tan; Leyuan Wang; Qijing Huang 001; Yida Wang; Michael W. Mahoney; Kurt Keutzer (ICML, 2021)

Characterizing possible failure modes in physics-informed neural networks. - Aditi S. Krishnapriyan; Amir Gholami; Shandian Zhe; Robert M. Kirby; Michael W. Mahoney (NeurIPS, 2021)

Hessian-Aware Pruning and Optimal Neural Implant. - Shixing Yu; Zhewei Yao; Amir Gholami; Zhen Dong 003; Michael W. Mahoney; Kurt Keutzer (CoRR, 2021)

A Survey of Quantization Methods for Efficient Neural Network Inference. - Amir Gholami; Sehoon Kim 001; Zhen Dong 003; Zhewei Yao; Michael W. Mahoney; Kurt Keutzer (CoRR, 2021)

Q-ASR: Integer-only Zero-shot Quantization for Efficient Speech Recognition. - Sehoon Kim 001; Amir Gholami; Zhewei Yao; Aniruddha Nrusimha; Bohan Zhai; Tianren Gao; Michael W. Mahoney; Kurt Keutzer (CoRR, 2021)

Learned Token Pruning for Transformers. - Sehoon Kim 001; Sheng Shen 001; David Thorsley; Amir Gholami; Joseph Hassoun; Kurt Keutzer (CoRR, 2021)

Applications and Techniques for Fast Machine Learning in Science. - Allison McCarn Deiana; Nhan Tran; Joshua Agar; Michaela Blott; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Scott Hauck; Mia Liu; Mark S. Neubauer; Jennifer Ngadiuba; Seda Ogrenci Memik; et al. (CoRR, 2021)

Integer-Only Zero-Shot Quantization for Efficient Speech Recognition. - Sehoon Kim 001; Amir Gholami; Zhewei Yao; Nicholas Lee; Patrick Wang; Aniruddha Nrusimha; Bohan Zhai; Tianren Gao; Michael W. Mahoney; Kurt Keutzer (ICASSP, 2022)

Learned Token Pruning for Transformers. - Sehoon Kim 001; Sheng Shen 001; David Thorsley; Amir Gholami; Woosuk Kwon; Joseph Hassoun; Kurt Keutzer (KDD, 2022)

Squeezeformer: An Efficient Transformer for Automatic Speech Recognition. - Sehoon Kim 001; Amir Gholami; Albert E. Shaw; Nicholas Lee; Karttikeya Mangalam; Jitendra Malik; Michael W. Mahoney; Kurt Keutzer (NeurIPS, 2022)

A Fast Post-Training Pruning Framework for Transformers. - Woosuk Kwon; Sehoon Kim 001; Michael W. Mahoney; Joseph Hassoun; Kurt Keutzer; Amir Gholami (NeurIPS, 2022)

Hessian-Aware Pruning and Optimal Neural Implant. - Shixing Yu; Zhewei Yao; Amir Gholami; Zhen Dong 003; Sehoon Kim 001; Michael W. Mahoney; Kurt Keutzer (WACV, 2022)

Applications and Techniques for Fast Machine Learning in Science. - Allison McCarn Deiana; Nhan Tran; Joshua Agar; Michaela Blott; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Scott Hauck; Mia Liu; Mark S. Neubauer; Jennifer Ngadiuba; Seda Ogrenci Memik; et al. (Frontiers Big Data, 2022)

Road accident risk prediction using generalized regression neural network optimized with self-organizing map. - Neda Kaffash-Charandabi; Amir Gholami; Ali Abdollahzadeh Bina (Neural Comput. Appl., 2022)

Adaptive Self-Supervision Algorithms for Physics-Informed Neural Networks. - Shashank Subramanian; Robert M. Kirby; Michael W. Mahoney; Amir Gholami (ECAI, 2023)

Speculative Decoding with Big Little Decoder. - Sehoon Kim 001; Karttikeya Mangalam; Suhong Moon; Jitendra Malik; Michael W. Mahoney; Amir Gholami; Kurt Keutzer (NeurIPS, 2023)

Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior. - Shashank Subramanian; Peter Harrington; Kurt Keutzer; Wahid Bhimji; Dmitriy Morozov; Michael W. Mahoney; Amir Gholami (NeurIPS, 2023)

Big Little Transformer Decoder. - Sehoon Kim 001; Karttikeya Mangalam; Jitendra Malik; Michael W. Mahoney; Amir Gholami; Kurt Keutzer (CoRR, 2023)

Full Stack Optimization of Transformer Inference: a Survey. - Sehoon Kim 001; Coleman Hooper; Thanakul Wattanawong; Minwoo Kang; Ruohan Yan; Hasan Genc; Grace Dinh; Qijing Huang 001; Kurt Keutzer; Michael W. Mahoney; Yakun Sophia Shao; Amir Gholami (CoRR, 2023)

End-to-end codesign of Hessian-aware quantized neural networks for FPGAs and ASICs. - Javier Campos; Zhen Dong 003; Javier M. Duarte; Amir Gholami; Michael W. Mahoney; Jovan Mitrevski; Nhan Tran (CoRR, 2023)

SPEED: Speculative Pipelined Execution for Efficient Decoding. - Coleman Hooper; Sehoon Kim 001; Hiva Mohammadzadeh; Hasan Genc; Kurt Keutzer; Amir Gholami; Yakun Sophia Shao (CoRR, 2023)

LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement. - Nicholas Lee; Thanakul Wattanawong; Sehoon Kim 001; Karttikeya Mangalam; Sheng Shen 001; Gopala Anumanchipalli; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (ACL (Findings), 2024)

SqueezeLLM: Dense-and-Sparse Quantization. - Sehoon Kim 001; Coleman Hooper; Amir Gholami; Zhen Dong 003; Xiuyu Li; Sheng Shen 001; Michael W. Mahoney; Kurt Keutzer (ICML, 2024)

An LLM Compiler for Parallel Function Calling. - Sehoon Kim 001; Suhong Moon; Ryan Tabrizi; Nicholas Lee; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (ICML, 2024)

KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization. - Coleman Hooper; Sehoon Kim 001; Hiva Mohammadzadeh; Michael W. Mahoney; Yakun Sophia Shao; Kurt Keutzer; Amir Gholami (NeurIPS, 2024)

Reliable edge machine learning hardware for scientific applications. - Tommaso Baldi; Javier Campos; Benjamin Hawks; Jennifer Ngadiuba; Nhan Tran; Daniel Diaz 003; Javier M. Duarte; Ryan Kastner; Andres Meza 001; Melissa Quinnan; Olivia Weng; Caleb Geniesse; et al. (VTS, 2024)

Characterizing Prompt Compression Methods for Long Context Inference. - Siddharth Jha; Lutfi Eren Erdogan; Sehoon Kim 001; Kurt Keutzer; Amir Gholami (CoRR, 2024)

TinyAgent: Function Calling at the Edge. - Lutfi Eren Erdogan; Nicholas Lee; Siddharth Jha; Sehoon Kim 001; Ryan Tabrizi; Suhong Moon; Coleman Hooper; Gopala Anumanchipalli; Kurt Keutzer; Amir Gholami (CoRR, 2024)

Efficient and Scalable Estimation of Tool Representations in Vector Space. - Suhong Moon; Siddharth Jha; Lutfi Eren Erdogan; Sehoon Kim 001; Woosang Lim; Kurt Keutzer; Amir Gholami (CoRR, 2024)

Squeezed Attention: Accelerating Long Context Length LLM Inference. - Coleman Hooper; Sehoon Kim 001; Hiva Mohammadzadeh; Monishwaran Maheswaran; June Paik; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (CoRR, 2024)

Corrigendum: Applications and techniques for fast machine learning in science. - Allison McCarn Deiana; Nhan Tran; Joshua Agar; Michaela Blott; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Scott Hauck; Mia Liu; Mark S. Neubauer; Jennifer Ngadiuba; Seda Ogrenci-Memik; et al. (Frontiers Big Data, 2024)

AI and Memory Wall. - Amir Gholami; Zhewei Yao; Sehoon Kim 001; Coleman Hooper; Michael W. Mahoney; Kurt Keutzer (IEEE Micro, 2024)

Multi-Source Data Aggregation and Real-Time Anomaly Classification and Localization in Power Distribution Systems. - Mehdi Ganjkhani; Amir Gholami; Jairo Giraldo; Anurag K. Srivastava 001; Masood Parvania (IEEE Trans. Smart Grid, 2024)

ORCA: Outage Root Cause Analysis in DER-Rich Power Distribution System Using Data Fusion, Hierarchical Clustering and FP-Growth Rule Mining. - Amir Gholami; Anurag Srivastava 001 (IEEE Trans. Smart Grid, 2024)

Spatio-Temporal Deep Graph Network for Event Detection, Localization, and Classification in Cyber-Physical Electric Distribution System. - Arman Ahmed; Sagnik Basumallik; Amir Gholami; Sajan K. Sadanandan; Mohammad Hossein Namaki; Anurag K. Srivastava 001; Yinghui Wu 001 (IEEE Trans. Ind. Informatics, 2024)

Detection and Classification of Anomalies in Power Distribution System Using Outlier Filtered Weighted Least Square. - Amir Gholami; Ashutosh Tiwari 003; Chuan Qin 004; Sanjeev Pannala; Anurag Srivastava 001; Roshan Sharma 002; Shikhar Pandey; Farnoosh Rahmatian (IEEE Trans. Ind. Informatics, 2024)

End-to-end codesign of Hessian-aware quantized neural networks for FPGAs. - Javier Campos; Jovan Mitrevski; Nhan Tran; Zhen Dong 003; Amir Gholaminejad; Michael W. Mahoney; Javier M. Duarte (ACM Trans. Reconfigurable Technol. Syst., 2024)

Squeezed Attention: Accelerating Long Context Length LLM Inference. - Coleman Richard Charles Hooper; Sehoon Kim 001; Hiva Mohammadzadeh; Monishwaran Maheswaran; Sebastian Zhao; June Paik; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (ACL (1), 2025)

QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache. - Rishabh Tiwari; Haocheng Xi; Aditya Tomar; Coleman Hooper; Sehoon Kim 001; Maxwell Horton; Mahyar Najibi; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (CoRR, 2025)

ETS: Efficient Tree Search for Inference-Time Scaling. - Coleman Hooper; Sehoon Kim 001; Suhong Moon; Kerem Dilmen; Monishwaran Maheswaran; Nicholas Lee; Michael W. Mahoney; Yakun Sophia Shao; Kurt Keutzer; Amir Gholami (CoRR, 2025)

Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks. - Lutfi Eren Erdogan; Nicholas Lee; Sehoon Kim 001; Suhong Moon; Hiroki Furuta; Gopala Anumanchipalli; Kurt Keutzer; Amir Gholami (CoRR, 2025)

Multipole Attention for Efficient Long Context Reasoning. - Coleman Hooper; Sebastian Zhao; Luca Manolache; Sehoon Kim 001; Michael W. Mahoney; Yakun Sophia Shao; Kurt Keutzer; Amir Gholami (CoRR, 2025)

XQuant: Breaking the Memory Wall for LLM Inference with KV Cache Rematerialization. - Aditya Tomar; Coleman Hooper; Minjae Lee; Haocheng Xi; Rishabh Tiwari; Wonjun Kang; Luca Manolache; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (CoRR, 2025)