Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Prediction. - Kisuk Lee; Aleksandar Zlateski; Ashwin Vishwanathan; H. Sebastian Seung (NIPS, 2015)

Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Detection. - Kisuk Lee; Aleksandar Zlateski; Ashwin Vishwanathan; H. Sebastian Seung (CoRR, 2015)

Image Segmentation by Size-Dependent Single Linkage Clustering of a Watershed Basin Graph. - Aleksandar Zlateski; H. Sebastian Seung (CoRR, 2015)

ZNN - A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-core and Many-Core Shared Memory Machines. - Aleksandar Zlateski; Kisuk Lee; H. Sebastian Seung (IPDPS, 2016)

ZNNi: maximizing the inference throughput of 3D convolutional networks on CPUs and GPUs. - Aleksandar Zlateski; Kisuk Lee; H. Sebastian Seung (SC, 2016)

ZNNi - Maximizing the Inference Throughput of 3D Convolutional Networks on Multi-Core CPUs and GPUs. - Aleksandar Zlateski; Kisuk Lee; H. Sebastian Seung (CoRR, 2016)

Scalable algorithms for semi-automatic segmentation of electron microscopy images of the brain tissue. - Aleksandar Zlateski (2016)

Compile-time optimized and statically scheduled N-D convnet primitives for multi-core and many-core (Xeon Phi) CPUs. - Aleksandar Zlateski; H. Sebastian Seung (ICS, 2017)

A Multicore Path to Connectomics-on-Demand. - Alexander Matveev; Yaron Meirovitch; Hayk Saribekyan; Wiktor Jakubiuk; Tim Kaler; Gergely Ódor; David M. Budden; Aleksandar Zlateski; Nir Shavit (PPoPP, 2017)

Scalable training of 3D convolutional networks on multi- and many-cores. - Aleksandar Zlateski; Kisuk Lee; H. Sebastian Seung (J. Parallel Distributed Comput., 2017)

On the Importance of Label Quality for Semantic Segmentation. - Aleksandar Zlateski; Ronnachai Jaroensri; Prafull Sharma; Frédo Durand (CVPR, 2018)

Optimizing N-dimensional, winograd-based convolution for manycore CPUs. - Zhen Jia 001; Aleksandar Zlateski; Frédo Durand; Kai Li 001 (PPoPP, 2018)

FFT Convolutions are Faster than Winograd on Modern CPUs, Here is Why. - Aleksandar Zlateski; Zhen Jia 001; Kai Li 001; Frédo Durand (CoRR, 2018)

PZnet: Efficient 3D ConvNet Inference on Manycore CPUs. - Sergiy Popovych; Davit Buniatyan; Aleksandar Zlateski; Kai Li 001; H. Sebastian Seung (CVC (1), 2019)

The anatomy of efficient FFT and winograd convolutions on modern CPUs. - Aleksandar Zlateski; Zhen Jia 001; Kai Li 001; Frédo Durand (ICS, 2019)

L3 Fusion: Fast Transformed Convolutions on CPUs. - Rati Gelashvili; Nir Shavit; Aleksandar Zlateski (CoRR, 2019)

Large-scale image segmentation based on distributed clustering algorithms. - Ran Lu; Aleksandar Zlateski; H. Sebastian Seung (CoRR, 2021)

LoopStack: a Lightweight Tensor Algebra Compiler Stack. - Bram Wasti; José Pablo Cambronero; Benoit Steiner; Hugh Leather; Aleksandar Zlateski (CoRR, 2022)

LoopTune: Optimizing Tensor Computations with Reinforcement Learning. - Dejan Grubisic; Bram Wasti; Chris Cummins; John M. Mellor-Crummey; Aleksandar Zlateski (CoRR, 2023)

Deferred Objects to Enhance Smart Contract Programming with Optimistic Parallel Execution. - George Mitenkov; Igor Kabiljo; Zekun Li 009; Alexander Spiegelman; Satyanarayana Vusirikala; Zhuolun Xiang; Aleksandar Zlateski; Nuno P. Lopes; Rati Gelashvili (CoRR, 2024)