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Zitiert von
Jahr
On the expressive power of deep learning: A tensor analysis
N Cohen, O Sharir, A Shashua
Conference on Learning Theory, 698-728, 2016
5922016
Quantum entanglement in deep learning architectures
Y Levine, O Sharir, N Cohen, A Shashua
Physical Review Letters 122 (6), 065301, 2019
2822019
The Cost of Training NLP Models: A Concise Overview
O Sharir, B Peleg, Y Shoham
arXiv preprint arXiv:2004.08900, 2020
275*2020
Deep autoregressive models for the efficient variational simulation of many-body quantum systems
O Sharir, Y Levine, N Wies, G Carleo, A Shashua
Physical Review Letters 124 (2), 020503, 2020
2692020
SenseBERT: Driving Some Sense into BERT
Y Levine, B Lenz, O Dagan, O Ram, D Padnos, O Sharir, ...
The 58th Annual Meeting of the Association for Computational Linguistics, 2020
2422020
Jurassic-1: Technical details and evaluation
O Lieber, O Sharir, B Lenz, Y Shoham
White Paper. AI21 Labs, 2021
2042021
Neural tensor contractions and the expressive power of deep neural quantum states
O Sharir, A Shashua, G Carleo
Physical Review B 106 (20), 205136, 2022
852022
Mathematical Aspects of Deep Learning
P Grohs, G Kutyniok
Cambridge University Press, 2022
832022
Limits to Depth Efficiencies of Self-Attention
Y Levine, N Wies, O Sharir, H Bata, A Shashua
34th Conference on Neural Information Processing Systems, 2020
57*2020
On the Expressive Power of Overlapping Architectures of Deep Learning
O Sharir, A Shashua
6th International Conference on Learning Representations, 2018
57*2018
Deep simnets
N Cohen, O Sharir, A Shashua
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
562016
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions
N Cohen, O Sharir, Y Levine, R Tamari, D Yakira, A Shashua
Intel Collaborative Research Institute for Computational Intelligence (ICRI …, 2017
47*2017
Tensorial mixture models
O Sharir, R Tamari, N Cohen, A Shashua
arXiv preprint arXiv:1610.04167, 2016
41*2016
Tensors for deep learning theory: Analyzing deep learning architectures via tensorization
Y Levine, N Wies, O Sharir, N Cohen, A Shashua
Tensors for Data Processing, 215-248, 2022
32*2022
Benefits of depth for long-term memory of recurrent networks
Y Levine, O Sharir, A Shashua
6th International Conference on Learning Representations - Workshop Track, 2018
272018
Sum-Product-Quotient Networks
O Sharir, A Shashua
The 21st International Conference on Artificial Intelligence and Statistics …, 2018
232018
Technical Report: Auxiliary Tuning and its Application to Conditional Text Generation
Y Zeldes, D Padnos, O Sharir, B Peleg
arXiv preprint arXiv:2006.16823, 2020
182020
Towards Neural Variational Monte Carlo That Scales Linearly with System Size
O Sharir, GK Chan, A Anandkumar
arXiv preprint arXiv:2212.11296, 2022
8*2022
On the Long-Term Memory of Deep Recurrent Networks
Y Levine, O Sharir, A Ziv, A Shashua
arXiv preprint arXiv:1710.09431, 2017
82017
ChatGPT Based Data Augmentation for Improved Parameter-Efficient Debiasing of LLMs
P Han, R Kocielnik, A Saravanan, R Jiang, O Sharir, A Anandkumar
arXiv preprint arXiv:2402.11764, 2024
62024
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