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Igor Krawczuk
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Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims
M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ...
https://arxiv.org/abs/2004.07213, 2020
3272020
Digress: Discrete denoising diffusion for graph generation
C Vignac, I Krawczuk, A Siraudin, B Wang, V Cevher, P Frossard
arXiv preprint arXiv:2209.14734, 2022
1772022
Meditron-70b: Scaling medical pretraining for large language models
Z Chen, AH Cano, A Romanou, A Bonnet, K Matoba, F Salvi, ...
arXiv preprint arXiv:2311.16079, 2023
462023
Filling gaps in trustworthy development of AI
S Avin, H Belfield, M Brundage, G Krueger, J Wang, A Weller, ...
Science 374 (6573), 1327-1329, 2021
302021
Toward trustworthy AI development: mechanisms for supporting verifiable claims (2020)
M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ...
arXiv preprint arXiv:2004.07213, 2020
172020
GG-GAN: A geometric graph generative adversarial network, 2021
I Krawczuk, P Abranches, A Loukas, V Cevher
https://openreview.net/forum?id=qiAxL3Xqx1o, 2020
12*2020
Effect of metal buffer layer and thermal annealing on HfOx-based ReRAMs
J Sandrini, B Attarimashalkoubeh, E Shahrabi, I Krawczuk, Y Leblebici
2016 IEEE International Conference on the Science of Electrical Engineering …, 2016
122016
Multi-ReRAM synapses for artificial neural network training
I Boybat, C Giovinazzo, E Shahrabi, I Krawczuk, I Giannopoulos, ...
2019 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2019
112019
Toward trustworthy AI development: Mechanisms for supporting verifiable claims. arXiv 2020
M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ...
arXiv preprint arXiv:2004.07213, 2004
112004
Proximal point imitation learning
L Viano, A Kamoutsi, G Neu, I Krawczuk, V Cevher
Advances in Neural Information Processing Systems 35, 24309-24326, 2022
72022
Finding actual descent directions for adversarial training
F Latorre, I Krawczuk, LT Dadi, TM Pethick, V Cevher
11th International Conference on Learning Representations (ICLR), 2023
52023
Uncertainty-driven adaptive sampling via GANs
T Sanchez, I Krawczuk, Z Sun, V Cevher
NeurIPS 2020 Workshop on Deep Learning and Inverse Problems, 2020
52020
Closed loop deep Bayesian inversion: Uncertainty driven acquisition for fast MRI
T Sanchez, I Krawczuk, Z Sun, V Cevher
32019
Distributed extra-gradient with optimal complexity and communication guarantees
A Ramezani-Kebrya, K Antonakopoulos, I Krawczuk, J Deschenaux, ...
arXiv preprint arXiv:2308.09187, 2023
12023
A Computational Turn in Policy Process Studies: Coevolving Network Dynamics of Policy Change
M Stauffer, I Mengesha, K Seifert, I Krawczuk, J Fischer, ...
Complexity 2022, 1-17, 2022
12022
Method for interfacing with hardware accelerators
C Piveteau, N Ioannou, I Krawczuk, M Le Gallo-Bourdeau, A Sebastian, ...
US Patent 11,250,107, 2022
12022
MEDITRON: Open Medical Foundation Models Adapted for Clinical Practice
A Bosselut, Z Chen, A Romanou, A Bonnet, A Hernández-Cano, ...
2024
Supplementary material A Computational Turn in Policy Process Studies: Co-evolving Network Dynamics of Policy Change
M Stauffer, I Mengesha, K Seifert, I Krawczuk, J Fischer, GDM Serugendo
2022
On the benefits of deep RL in accelerated MRI sampling
T Sanchez, I Krawczuk, V Cevher
2021
Computational Policy Process Studies
M Stauffer, K Seifert, I Mengesha, I Krawczuk, J Fischer, GDM Serugendo
2021
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Articles 1–20