- Ehab Abdelhamid, Amirhossein Aleyasen, Michael Duller, Eric Foratier, Vincent Fruleux, Mirella Katch, Gourab Mitra, Rima Mutreja, Jozsef Patvarczki, Matthew Pope, Nikos Tsikoudis, F. Michael Waas:
How Global Retailer ADEO Migrated to Google BigQuery with Database Virtualization. IEEE Big Data 2023: 1895-1898 - Guy Amir, Osher Maayan, Tom Zelazny, Guy Katz, Michael Schapira:
Verifying Generalization in Deep Learning. CAV (2) 2023: 438-455 - Michael Amir, Yigal Koifman, Yakov Bloch, Ariel Barel, Alfred M. Bruckstein:
Multi-Agent Distributed and Decentralized Geometric Task Allocation. CDC 2023: 8355-8362 - Andreas Koch, Michael Petry, Max Ghiglione, Amir Raoofy, Gabriel Dax, Gianluca Furano, Martin Werner, Carsten Trinitis, Martin Langer:
Machine Learning Application Benchmark. CF 2023: 229-235 - Julian Scheipl, Amir Raoofy, Michael Ott, Josef Weidendorfer:
Phase-aware System-Side Sampling for HPC. CF 2023: 220-221 - Marcos V. Conde, Manuel Kolmet, Tim Seizinger, Tom E. Bishop, Radu Timofte, Xiangyu Kong, Dafeng Zhang, Jinlong Wu, Fan Wang, Juewen Peng, Zhiyu Pan, Chengxin Liu, Xianrui Luo, Huiqiang Sun, Liao Shen, Zhiguo Cao, Ke Xian, Chaowei Liu, Zigeng Chen, Xingyi Yang, Songhua Liu, Yongcheng Jing, Michael Bi Mi, Xinchao Wang, Zhihao Yang, Wenyi Lian, Siyuan Lai, Haichuan Zhang, Trung Hoang, Amirsaeed Yazdani, Vishal Monga, Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, Thomas B. Schön, Yuxuan Zhao, Baoliang Chen, Yiqing Xu, JiXiangNiu:
Lens-to-Lens Bokeh Effect Transformation. NTIRE 2023 Challenge Report. CVPR Workshops 2023: 1643-1659 - Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney, Amir Gholami:
Adaptive Self-Supervision Algorithms for Physics-Informed Neural Networks. ECAI 2023: 2234-2241 - Ben Eyal, Moran Mahabi, Ophir Haroche, Amir Bachar, Michael Elhadad:
Semantic Decomposition of Question and SQL for Text-to-SQL Parsing. EMNLP (Findings) 2023: 13629-13645 - Reyhaneh Rabaninejad, Behzad Abdolmaleki, Giulio Malavolta, Antonis Michalas, Amir Nabizadeh:
stoRNA: Stateless Transparent Proofs of Storage-time. ESORICS (3) 2023: 389-410 - Alon Shats, Michael Amir, Noa Agmon:
Competitive Ant Coverage: The Value of Pursuit. IROS 2023: 6733-6740 - Aryan Ghazipour, Tyler Settle, Benjamin Veasey, Emily Daugherty, Samuel Keltner, Nitin Kumar, James Ververs, Michael Farris, Neal Dunlap, Amir A. Amini:
Survival Outcome Prediction for Stereotactic Body Radiation Therapy of Lung Cancer from Post-RT Ct Images with RNN/CNN Deep Learning. ISBI 2023: 1-4 - Anirudh Potlapally, Shubham Mahajan, Michael Briden, Harrison Shawa, Andrea Medina Lopez, Daniel Yoon, Amir Mazaheri, Hsinya Yang, Sara Dahle, Roslyn R. Isseroff, Narges Norouzi:
WoundNet: A Domain-Adaptable Few-Shot Classification Framework for Wound Healing Assessment. ISBI 2023: 1-5 - Wei-Lun Huang, Davood Tashayyod, Jun Kang, Amir Gandjbakhche, Michael Kazhdan, Mehran Armand:
Skin Lesion Correspondence Localization in Total Body Photography. MICCAI (7) 2023: 260-269 - Hooman Vaseli, Ang Nan Gu, S. Neda Ahmadi Amiri, Michael Y. Tsang, Andrea Fung, Nima Kondori, Armin Saadat, Purang Abolmaesumi, Teresa S. M. Tsang:
ProtoASNet: Dynamic Prototypes for Inherently Interpretable and Uncertainty-Aware Aortic Stenosis Classification in Echocardiography. MICCAI (6) 2023: 368-378 - Amir Torabi, George Sklivanitis, Dimitris A. Pados, Elizabeth Serena Bentley, Joseph Suprenant, Michael J. Medley:
Interference-Avoiding RFSoC-based MIMO Links. MILCOM 2023: 249-250 - Sehoon Kim, Karttikeya Mangalam, Suhong Moon, Jitendra Malik, Michael W. Mahoney, Amir Gholami, Kurt Keutzer:
Speculative Decoding with Big Little Decoder. NeurIPS 2023 - Shashank Subramanian, Peter Harrington, Kurt Keutzer, Wahid Bhimji, Dmitriy Morozov, Michael W. Mahoney, Amir Gholami:
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior. NeurIPS 2023 - Mohak Chadha, Eishi Arima, Amir Raoofy, Michael Gerndt, Martin Schulz:
Sustainability in HPC: Vision and Opportunities. SC Workshops 2023: 1876-1880 - Karl Bringmann, Michael Kapralov, Mikhail Makarov, Vasileios Nakos, Amir Yagudin, Amir Zandieh:
Traversing the FFT Computation Tree for Dimension-Independent Sparse Fourier Transforms. SODA 2023: 4768-4845 - Guy Amir, Osher Maayan, Tom Zelazny, Guy Katz, Michael Schapira:
Verifying Generalization in Deep Learning. CoRR abs/2302.05745 (2023) - Sehoon Kim, Karttikeya Mangalam, Jitendra Malik, Michael W. Mahoney, Amir Gholami, Kurt Keutzer:
Big Little Transformer Decoder. CoRR abs/2302.07863 (2023) - Sehoon Kim, Coleman Hooper, Thanakul Wattanawong, Minwoo Kang, Ruohan Yan, Hasan Genc, Grace Dinh, Qijing Huang, Kurt Keutzer, Michael W. Mahoney, Yakun Sophia Shao, Amir Gholami:
Full Stack Optimization of Transformer Inference: a Survey. CoRR abs/2302.14017 (2023) - Mohammad Sadegh Nasr, Amir Hajighasemi, Paul Koomey, Parisa Boodaghi Malidarreh, Michael Robben, Jillur Rahman Saurav, Helen H. Shang, Manfred Huber, Jacob M. Luber:
Clinically Relevant Latent Space Embedding of Cancer Histopathology Slides through Variational Autoencoder Based Image Compression. CoRR abs/2303.13332 (2023) - Jason Yik, Soikat Hasan Ahmed, Zergham Ahmed, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Douwe den Blanken, Petrut Bogdan, Sander M. Bohté, Younes Bouhadjar, Sonia M. Buckley, Gert Cauwenberghs, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Reddy Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Jeremy Forest, Steve B. Furber, Michael Furlong, Aditya Gilra, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Gregor Lenz, Rajit Manohar, Christian Mayr, Konstantinos P. Michmizos, Dylan R. Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayça Özcelikkale, Noah Pacik-Nelson, Priyadarshini Panda, Pao-Sheng Sun, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Catherine D. Schuman, Jae-sun Seo, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Michael Stewart, Terrence C. Stewart, Philipp Stratmann, Guangzhi Tang, Jonathan Timcheck, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Biyan Zhou, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi:
NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. CoRR abs/2304.04640 (2023) - Javier Campos, Zhen Dong, Javier M. Duarte, Amir Gholami, Michael W. Mahoney, Jovan Mitrevski, Nhan Tran:
End-to-end codesign of Hessian-aware quantized neural networks for FPGAs and ASICs. CoRR abs/2304.06745 (2023) - Shashank Subramanian, Peter Harrington, Kurt Keutzer, Wahid Bhimji, Dmitriy Morozov, Michael W. Mahoney, Amir Gholami:
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior. CoRR abs/2306.00258 (2023) - Amir Hajighasemi, Md Jillur Rahman Saurav, Mohammad Sadegh Nasr, Jai Prakash Veerla, Aarti Darji, Parisa Boodaghi Malidarreh, Michael Robben, Helen H. Shang, Jacob M. Luber:
Multimodal Pathology Image Search Between H&E Slides and Multiplexed Immunofluorescent Images. CoRR abs/2306.06780 (2023) - Sehoon Kim, Coleman Hooper, Amir Gholami, Zhen Dong, Xiuyu Li, Sheng Shen, Michael W. Mahoney, Kurt Keutzer:
SqueezeLLM: Dense-and-Sparse Quantization. CoRR abs/2306.07629 (2023)