224 citations · 332 across the 10 of their papers we have counts for
11 papers
Discovering Mechanistic Models of Neural Activity: System Identification in an in Silico Zebrafish
Jan-Matthis Lueckmann, Viren Jain, Michał Januszewski
Constructing mechanistic models of neural circuits is a fundamental goal of neuroscience, yet verifying such models is limited by the lack of ground truth. To rigorously test model…
ZAPBench: A Benchmark for Whole-Brain Activity Prediction in Zebrafish
Jan-Matthis Lueckmann, Alexander Immer, Alex Bo-Yuan Chen +15
Data-driven benchmarks have led to significant progress in key scientific modeling domains including weather and structural biology. Here, we introduce the Zebrafish Activity Predi…
Forecasting Whole-Brain Neuronal Activity from Volumetric Video
Alexander Immer, Jan-Matthis Lueckmann, Alex Bo-Yuan Chen +14
Large-scale neuronal activity recordings with fluorescent calcium indicators are increasingly common, yielding high-resolution 2D or 3D videos. Traditional analysis pipelines reduc…
Adversarial Image Alignment and Interpolation
Viren Jain
Volumetric (3d) images are acquired for many scientific and biomedical purposes using imaging methods such as serial section microscopy, CT scans, and MRI. A frequent step in the a…
Superhuman Accuracy on the SNEMI3D Connectomics Challenge
Kisuk Lee, Jonathan Zung, Peter Li +2
For the past decade, convolutional networks have been used for 3D reconstruction of neurons from electron microscopic (EM) brain images. Recent years have seen great improvements i…
Morphological Error Detection in 3D Segmentations
David Rolnick, Yaron Meirovitch, Toufiq Parag +5
Deep learning algorithms for connectomics rely upon localized classification, rather than overall morphology. This leads to a high incidence of erroneously merged objects. Humans,…
Flood-Filling Networks
Michał Januszewski, Jeremy Maitin-Shepard, Peter Li +3
State-of-the-art image segmentation algorithms generally consist of at least two successive and distinct computations: a boundary detection process that uses local image informatio…
Grand Challenges for Global Brain Sciences
Joshua T. Vogelstein, Katrin Amunts, Andreas Andreou +59
The next grand challenges for society and science are in the brain sciences. A collection of 60+ scientists from around the world, together with 10+ observers from national, privat…
Combinatorial Energy Learning for Image Segmentation
Jeremy Maitin-Shepard, Viren Jain, Michal Januszewski +2
We introduce a new machine learning approach for image segmentation that uses a neural network to model the conditional energy of a segmentation given an image. Our approach, combi…
Learned versus Hand-Designed Feature Representations for 3d Agglomeration
John A. Bogovic, Gary B. Huang, Viren Jain
For image recognition and labeling tasks, recent results suggest that machine learning methods that rely on manually specified feature representations may be outperformed by method…
Deep and Wide Multiscale Recursive Networks for Robust Image Labeling
Gary B. Huang, Viren Jain
Feedforward multilayer networks trained by supervised learning have recently demonstrated state of the art performance on image labeling problems such as boundary prediction and sc…