Tijmen Blankevoort
Tijmen Blankevoort
Qualcomm AI Research
Verified email at qti.qualcomm.com
Title
Cited by
Cited by
Year
Data-free quantization through weight equalization and bias correction
M Nagel, M Baalen, T Blankevoort, M Welling
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
1032019
Relaxed quantization for discretized neural networks
C Louizos, M Reisser, T Blankevoort, E Gavves, M Welling
arXiv preprint arXiv:1810.01875, 2018
742018
Conditional channel gated networks for task-aware continual learning
D Abati, J Tomczak, T Blankevoort, S Calderara, R Cucchiara, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
222020
Batch-shaping for learning conditional channel gated networks
BE Bejnordi, T Blankevoort, M Welling
arXiv preprint arXiv:1907.06627, 2019
202019
Up or down? adaptive rounding for post-training quantization
M Nagel, RA Amjad, M Van Baalen, C Louizos, T Blankevoort
International Conference on Machine Learning, 7197-7206, 2020
172020
Gradient Regularization for Quantization Robustness
M Alizadeh, A Behboodi, M van Baalen, C Louizos, T Blankevoort, ...
arXiv preprint arXiv:2002.07520, 2020
112020
Bayesian bits: Unifying quantization and pruning
M van Baalen, C Louizos, M Nagel, RA Amjad, Y Wang, T Blankevoort, ...
arXiv preprint arXiv:2005.07093, 2020
92020
Taxonomy and evaluation of structured compression of convolutional neural networks
A Kuzmin, M Nagel, S Pitre, S Pendyam, T Blankevoort, M Welling
arXiv preprint arXiv:1912.09802, 2019
92019
LSQ+: Improving low-bit quantization through learnable offsets and better initialization
Y Bhalgat, J Lee, M Nagel, T Blankevoort, N Kwak
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
82020
Differentiable joint pruning and quantization for hardware efficiency
Y Wang, Y Lu, T Blankevoort
European Conference on Computer Vision, 259-277, 2020
52020
Learned threshold pruning
K Azarian, Y Bhalgat, J Lee, T Blankevoort
arXiv preprint arXiv:2003.00075, 2020
52020
Continuous relaxation of quantization for discretized deep neural networks
C Louizos, M Reisser, TPF Blankevoort, M Welling
US Patent App. 16/413,535, 2019
22019
Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces
B Moons, P Noorzad, A Skliar, G Mariani, D Mehta, C Lott, T Blankevoort
arXiv preprint arXiv:2012.08859, 2020
12020
Analytic And Empirical Correction Of Biased Error Introduced By Approximation Methods
MW Van Baalen, TPF Blankevoort, M Nagel
US Patent App. 16/826,472, 2020
12020
Learned threshold pruning for deep neural networks
KA Yazdi, TPF BLANKEVOORT, JW Lee, YS BHALGAT
US Patent App. 17/067,233, 2021
2021
Joint pruning and quantization scheme for deep neural networks
Y Lu, Y Wang, TPF Blankevoort, C Louizos, M Reisser, J Hou
US Patent App. 17/030,315, 2021
2021
Channel Gating For Conditional Computation
BE Bejnordi, TPF Blankevoort, M Welling
US Patent App. 16/419,509, 2020
2020
Systems and Methods of Cross Layer Rescaling for Improved Quantization Performance
M Nagel, MW Van Baalen, TPF Blankevoort
US Patent App. 16/826,524, 2020
2020
Data-aware layer decomposition for neural network compression
M Nagel, TPF Blankevoort
US Patent App. 16/299,375, 2020
2020
Batch-Shaping for Learning Conditional Channel Gated Networks
B Ehteshami Bejnordi, T Blankevoort, M Welling
arXiv e-prints, arXiv: 1907.06627, 2019
2019
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