Aleksandar Zlateski
Aleksandar Zlateski
Research Scientist - Facebook AI Research (FAIR)
Verified email at fb.com
Title
Cited by
Cited by
Year
Space–time wiring specificity supports direction selectivity in the retina
JS Kim, MJ Greene, A Zlateski, K Lee, M Richardson, SC Turaga, ...
Nature 509 (7500), 331-336, 2014
3812014
Recursive training of 2d-3d convolutional networks for neuronal boundary prediction
K Lee, A Zlateski, V Ashwin, HS Seung
Advances in Neural Information Processing Systems, 3573-3581, 2015
672015
ZNN--A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-core and Many-Core Shared Memory Machines
A Zlateski, K Lee, HS Seung
2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2016
412016
On the importance of label quality for semantic segmentation
A Zlateski, R Jaroensri, P Sharma, F Durand
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
312018
Image segmentation by size-dependent single linkage clustering of a watershed basin graph
A Zlateski, HS Seung
arXiv preprint arXiv:1505.00249, 2015
302015
Automated computation of arbor densities: a step toward identifying neuronal cell types
U Sümbül, A Zlateski, A Vishwanathan, RH Masland, HS Seung
Frontiers in neuroanatomy 8, 139, 2014
282014
ZNN i: maximizing the inference throughput of 3D convolutional networks on CPUs and GPUs
A Zlateski, K Lee, HS Seung
Proceedings of the International Conference for High Performance Computing …, 2016
212016
ZNNi: maximizing the inference throughput of 3D convolutional networks on CPUs and GPUs
A Zlateski, K Lee, HS Seung
SC'16: Proceedings of the International Conference for High Performance …, 2016
192016
A multicore path to connectomics-on-demand
A Matveev, Y Meirovitch, H Saribekyan, W Jakubiuk, T Kaler, G Odor, ...
Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of …, 2017
172017
Optimizing N-dimensional, winograd-based convolution for manycore CPUs
Z Jia, A Zlateski, F Durand, K Li
Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of …, 2018
142018
Compile-time optimized and statically scheduled ND convnet primitives for multi-core and many-core (Xeon Phi) CPUs
A Zlateski, HS Seung
Proceedings of the International Conference on Supercomputing, 1-10, 2017
112017
Scalable training of 3D convolutional networks on multi-and many-cores
A Zlateski, K Lee, HS Seung
Journal of Parallel and Distributed Computing 106, 195-204, 2017
92017
Fft convolutions are faster than winograd on modern cpus, here is why
A Zlateski, Z Jia, K Li, F Durand
arXiv preprint arXiv:1809.07851, 2018
52018
Chandelier cell anatomy and function reveal a variably distributed but common signal
CM Schneider-Mizell, AL Bodor, F Collman, D Brittain, AA Bleckert, ...
bioRxiv, 2020
42020
Pznet: Efficient 3d convnet inference on manycore cpus
S Popovych, D Buniatyan, A Zlateski, K Li, HS Seung
Science and Information Conference, 369-383, 2019
42019
A design and implementation of an efficient, parallel watershed algorithm for affinity graphs
A Zlateski
Massachusetts Institute of Technology, 2011
42011
The anatomy of efficient FFT and winograd convolutions on modern CPUs
A Zlateski, Z Jia, K Li, F Durand
Proceedings of the ACM International Conference on Supercomputing, 414-424, 2019
32019
Binary and analog variation of synapses between cortical pyramidal neurons
S Dorkenwald, NL Turner, T Macrina, K Lee, R Lu, J Wu, AL Bodor, ...
BioRxiv, 2019
32019
Multiscale and multimodal reconstruction of cortical structure and function
NL Turner, T Macrina, JA Bae, R Yang, AM Wilson, C Schneider-Mizell, ...
bioRxiv, 2020
12020
Towards Optimal Winograd Convolution on Manycores
Z Jia, A Zlateski, F Durand, K Li
SysML 2018, 2018
12018
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