Andrzej Banburski - Fahey
Andrzej Banburski - Fahey
Principal Researcher, Microsoft Research
E-mail megerősítve itt: microsoft.com - Kezdőlap
Hivatkozott rá
Hivatkozott rá
Theoretical issues in deep networks
T Poggio, A Banburski, Q Liao
Proceedings of the National Academy of Sciences 117 (48), 30039-30045, 2020
Theory of deep learning III: Dynamics and generalization in deep networks
A Banburski, Q Liao, B Miranda, T Poggio, L Rosasco, B Liang, J Hidary
Center for Brains, Minds and Machines (CBMM) Memo No 90, 2019
Biologically inspired mechanisms for adversarial robustness
MR Vuyyuru, A Banburski, N Pant, T Poggio
Advances in Neural Information Processing Systems 33, 2135-2146, 2020
Production and discovery of true muonium in fixed-target experiments
A Banburski, P Schuster
Physical Review D 86 (9), 093007, 2012
Pachner moves in a 4d Riemannian holomorphic Spin Foam model
A Banburski, LQ Chen, L Freidel, J Hnybida
Physical Review D 92 (12), 124014, 2015
A surprising linear relationship predicts test performance in deep networks
Q Liao, B Miranda, A Banburski, J Hidary, T Poggio
arXiv preprint arXiv:1807.09659, 2018
Complexity control by gradient descent in deep networks
T Poggio, Q Liao, A Banburski
Nature communications 11 (1), 1027, 2020
Double descent in the condition number
T Poggio, G Kur, A Banburski
arXiv preprint arXiv:1912.06190, 2019
Theory IIIb: Generalization in deep networks
T Poggio, Q Liao, B Miranda, A Banburski, X Boix, J Hidary
arXiv preprint arXiv:1806.11379, 2018
Snyder momentum space in relative locality
A Banburski, L Freidel
Physical Review D 90 (7), 076010, 2014
Neural collapse in deep homogeneous classifiers and the role of weight decay
A Rangamani, A Banburski-Fahey
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
Neural-guided, bidirectional program search for abstraction and reasoning
S Alford, A Gandhi, A Rangamani, A Banburski, T Wang, S Dandekar, ...
Complex Networks & Their Applications X: Volume 1, Proceedings of the Tenth …, 2022
Math operations in mixed or virtual reality
J Lanier, A Banburski
US Patent 10,192,363, 2019
LLMR: Real-time Prompting of Interactive Worlds using Large Language Models
F De La Torre, CM Fang, H Huang, A Banburski-Fahey, JA Fernandez, ...
arXiv preprint arXiv:2309.12276, 2023
Reprompting: Automated chain-of-thought prompt inference through gibbs sampling
W Xu, A Banburski-Fahey, N Jojic
arXiv preprint arXiv:2305.09993, 2023
Deep classifiers trained with the square loss
M Xu, A Rangamani, A Banburski, Q Liao, T Galanti, T Poggio
Center for Brains, Minds and Machines (CBMM) Memo No 117, 2022
Steps towards prompt-based creation of virtual worlds
J Roberts, A Banburski-Fahey, J Lanier
arXiv preprint arXiv:2211.05875, 2022
Evaluating the adversarial robustness of a foveated texture transform module in a cnn
JM Gant, A Banburski, A Deza
SVRHM 2021 Workshop@ NeurIPS, 2021
Dreaming with ARC
A Banburski, A Ghandi, S Alford, S Dandekar, P Chin, T Poggio
NeurIPS 2020 LMCA Workshop, 2020
Hierarchically compositional tasks and deep convolutional networks
A Deza, Q Liao, A Banburski, T Poggio
arXiv preprint arXiv:2006.13915, 2020
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