Nir Shavit | DeepAI

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Featured Co-authors

Hao Wang
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∙ 03/02/2023

X-Ray2EM: Uncertainty-Aware Cross-Modality Image Reconstruction from X-Ray to Electron Microscopy in Connectomics

Comprehensive, synapse-resolution imaging of the brain will be crucial f...

0 Yicong Li, et al. ∙

∙ 02/14/2023

Cliff-Learning

We study the data-scaling of transfer learning from foundation models in...

0 Tony T. Wang, et al. ∙

∙ 02/08/2023

The XPRESS Challenge: Xray Projectomic Reconstruction – Extracting Segmentation with Skeletons

The wiring and connectivity of neurons form a structural basis for the f...

0 Tri Nguyen, et al. ∙

∙ 10/13/2021

Revisiting Latent-Space Interpolation via a Quantitative Evaluation Framework

Latent-space interpolation is commonly used to demonstrate the generaliz...

6 Lu Mi, et al. ∙

∙ 06/28/2021

HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps

High Definition (HD) maps are maps with precise definitions of road lane...

12 Lu Mi, et al. ∙

∙ 01/07/2021

Learning Guided Electron Microscopy with Active Acquisition

Single-beam scanning electron microscopes (SEM) are widely used to acqui...

5 Lu Mi, et al. ∙

∙ 06/18/2020

On the Predictability of Pruning Across Scales

We show that the error of magnitude-pruned networks follows a scaling la...

0 Jonathan S. Rosenfeld, et al. ∙

∙ 12/04/2019

L3 Fusion: Fast Transformed Convolutions on CPUs

Fast convolutions via transforms, either Winograd or FFT, had emerged as...

0 Rati Gelashvili, et al. ∙

∙ 09/27/2019

A Constructive Prediction of the Generalization Error Across Scales

The dependency of the generalization error of neural networks on model a...

11 Jonathan S. Rosenfeld, et al. ∙

∙ 12/04/2018

Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics

Pixel-accurate tracking of objects is a key element in many computer vis...

2 Yaron Meirovitch, et al. ∙

∙ 05/30/2017

Morphological Error Detection in 3D Segmentations

Deep learning algorithms for connectomics rely upon localized classifica...

0 David Rolnick, et al. ∙

∙ 05/30/2017

Deep Learning is Robust to Massive Label Noise

Deep neural networks trained on large supervised datasets have led to im...

0 David Rolnick, et al. ∙

∙ 03/04/2017

Generative Compression

Traditional image and video compression algorithms rely on hand-crafted ...

0 Shibani Santurkar, et al. ∙

∙ 02/23/2017

Toward Streaming Synapse Detection with Compositional ConvNets

Connectomics is an emerging field in neuroscience that aims to reconstru...

0 Shibani Santurkar, et al. ∙

∙ 12/07/2016

A Multi-Pass Approach to Large-Scale Connectomics

The field of connectomics faces unprecedented "big data" challenges. To ...

0 Yaron Meirovitch, et al. ∙

∙ 11/20/2016

Deep Tensor Convolution on Multicores

Deep convolutional neural networks (ConvNets) of 3-dimensional kernels a...

0 David Budden, et al. ∙

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