Yasaman Bahri
Yasaman Bahri
Research Scientist, Google Brain
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Deep neural networks as gaussian processes
J Lee, Y Bahri, R Novak, SS Schoenholz, J Pennington, J Sohl-Dickstein
arXiv preprint arXiv:1711.00165, 2017
3592017
Wide neural networks of any depth evolve as linear models under gradient descent
J Lee, L Xiao, SS Schoenholz, Y Bahri, R Novak, J Sohl-Dickstein, ...
arXiv preprint arXiv:1902.06720, 2019
2562019
Localization and topology protected quantum coherence at the edge of hot matter
Y Bahri, R Vosk, E Altman, A Vishwanath
Nature communications 6, 7341, 2015
1902015
Sensitivity and generalization in neural networks: an empirical study
R Novak, Y Bahri, DA Abolafia, J Pennington, J Sohl-Dickstein
arXiv preprint arXiv:1802.08760, 2018
1872018
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
L Xiao, Y Bahri, J Sohl-Dickstein, SS Schoenholz, J Pennington
https://arxiv.org/abs/1806.05393, 2018
1402018
Bayesian Convolutional Neural Networks with Many Channels are Gaussian Processes
R Novak, L Xiao, J Lee, Y Bahri, D Abolafia, J Pennington, ...
https://arxiv.org/abs/1810.05148, 2018
105*2018
Geometry of neural network loss surfaces via random matrix theory
J Pennington, Y Bahri
International Conference on Machine Learning, 2798-2806, 2017
822017
Phonon analog of topological nodal semimetals
HC Po, Y Bahri, A Vishwanath
Physical Review B 93 (20), 205158, 2016
402016
Spatial resolution of a type II heterojunction in a single bipolar molecule
C Tao, J Sun, X Zhang, R Yamachika, D Wegner, Y Bahri, G Samsonidze, ...
Nano letters 9 (12), 3963-3967, 2009
322009
Statistical mechanics of deep learning
Y Bahri, J Kadmon, J Pennington, SS Schoenholz, J Sohl-Dickstein, ...
Annual Review of Condensed Matter Physics, 2020
302020
The large learning rate phase of deep learning: the catapult mechanism
A Lewkowycz, Y Bahri, E Dyer, J Sohl-Dickstein, G Gur-Ari
arXiv preprint arXiv:2003.02218, 2020
222020
Detecting Majorana fermions in quasi-one-dimensional topological phases using nonlocal order parameters
Y Bahri, A Vishwanath
Physical review b 89 (15), 155135, 2014
192014
Stable non-Fermi-liquid phase of itinerant spin-orbit coupled ferromagnets
Y Bahri, AC Potter
Physical Review B 92 (3), 035131, 2015
62015
Infinite attention: NNGP and NTK for deep attention networks
J Hron, Y Bahri, J Sohl-Dickstein, R Novak
International Conference on Machine Learning, 4376-4386, 2020
52020
Bayesian deep convolutional neural networks with many channels are gaussian processes
R Novak, L Xiao, J Lee, Y Bahri, G Yang, D Abolafia, J Pennington, ...
22019
Wide neural networks of any depth evolve as linear models under gradient descent
J Lee, L Xiao, SS Schoenholz, Y Bahri, R Novak, J Sohl-Dickstein, ...
Journal of Statistical Mechanics: Theory and Experiment 2020 (12), 124002, 2020
12020
Exact posterior distributions of wide Bayesian neural networks
J Hron, Y Bahri, R Novak, J Pennington, J Sohl-Dickstein
arXiv preprint arXiv:2006.10541, 2020
12020
Quantum Phenomena in Interacting Many-Body Systems: Topological Protection, Localization, and Non-Fermi Liquids
Y Bahri
UC Berkeley, 2017
2017
Exact posterior distributions of wide Bayesian neural networks Download PDF
J Hron, Y Bahri, R Novak, J Pennington, J Sohl-Dickstein
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes Download PDF
R Novak, L Xiao, Y Bahri, J Lee, G Yang, J Hron, DA Abolafia, ...
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