Srinivas C. Turaga

Publication Activity (10 Years)

Years Active: 2007-2022
Publications (10 Years): 20

Top Topics

Electron Micrographs

Top Venues

IEEE Trans. Pattern Anal. Mach. Intell.

Publications

Lu Mi, Richard Xu, Sridhama Prakhya, Albert Lin, Nir Shavit, Aravinthan D. T. Samuel, Srinivas C. Turaga
Connectome-constrained Latent Variable Model of Whole-Brain Neural Activity. ICLR (2022)
Diptodip Deb, Zhenfei Jiao, Ruth R. Sims, Alex B. Chen, Michael Broxton, Misha B. Ahrens, Kaspar Podgorski, Srinivas C. Turaga
FourierNets enable the design of highly non-local optical encoders for computational imaging. NeurIPS (2022)
Diptodip Deb, Zhenfei Jiao, Alex B. Chen, Misha B. Ahrens, Kaspar Podgorski, Srinivas C. Turaga
Programmable 3D snapshot microscopy with Fourier convolutional networks. CoRR (2021)
Lu Mi, Hao Wang, Yaron Meirovitch, Richard Schalek, Srinivas C. Turaga, Jeff W. Lichtman, Aravinthan D. T. Samuel, Nir Shavit
Learning Guided Electron Microscopy with Active Acquisition. CoRR (2021)
Lu Mi, Hao Wang, Yaron Meirovitch, Richard Schalek, Srinivas C. Turaga, Jeff W. Lichtman, Aravinthan D. T. Samuel, Nir Shavit
Learning Guided Electron Microscopy with Active Acquisition. MICCAI (5) (2020)
Daniel Jiwoong Im, Sridhama Prakhya, Jinyao Yan, Srinivas C. Turaga, Kristin Branson
Importance Weighted Adversarial Variational Autoencoders for Spike Inference from Calcium Imaging Data. CoRR (2019)
Jan Funke, Fabian Tschopp, William Grisaitis, Arlo Sheridan, Chandan Singh, Stephan Saalfeld, Srinivas C. Turaga
Large Scale Image Segmentation with Structured Loss Based Deep Learning for Connectome Reconstruction. IEEE Trans. Pattern Anal. Mach. Intell. 41 (7) (2019)
Artur Speiser, Srinivas C. Turaga, Jakob H. Macke
Teaching deep neural networks to localize sources in super-resolution microscopy by combining simulation-based learning and unsupervised learning. CoRR (2019)
Julia M. Buhmann, Renate Krause, Rodrigo Ceballos Lentini, Nils Eckstein, Matthew Cook, Srinivas C. Turaga, Jan Funke
Synaptic partner prediction from point annotations in insect brains. CoRR (2018)
Julia M. Buhmann, Renate Krause, Rodrigo Ceballos Lentini, Nils Eckstein, Matthew Cook, Srinivas C. Turaga, Jan Funke
Synaptic Partner Prediction from Point Annotations in Insect Brains. MICCAI (2) (2018)
Laurence Aitchison, Vincent Adam, Srinivas C. Turaga
Discrete flow posteriors for variational inference in discrete dynamical systems. CoRR (2018)
Fabian David Tschopp, Michael B. Reiser, Srinivas C. Turaga
A Connectome Based Hexagonal Lattice Convolutional Network Model of the Drosophila Visual System. CoRR (2018)
Philipp Berens, Jeremy Freeman, Thomas Deneux, Nicolay Chenkov, Thomas McColgan, Artur Speiser, Jakob H. Macke, Srinivas C. Turaga, Patrick Mineault, Peter Rupprecht, Stephan Gerhard, Rainer W. Friedrich, Johannes Friedrich, Liam Paninski, Marius Pachitariu, Kenneth D. Harris, Ben Bolte, Timothy A. Machado, Dario Ringach, Jasmine Stone, Luke E. Rogerson, Nicolas J. Sofroniew, Jacob Reimer, Emmanouil Froudarakis, Thomas Euler, Miroslav Román Rosón, Lucas Theis, Andreas S. Tolias, Matthias Bethge
Community-based benchmarking improves spike rate inference from two-photon calcium imaging data. PLoS Comput. Biol. 14 (5) (2018)
Toufiq Parag, Fabian Tschopp, William Grisaitis, Srinivas C. Turaga, Xuewen Zhang, Brian Matejek, Lee Kamentsky, Jeff W. Lichtman, Hanspeter Pfister
Anisotropic EM Segmentation by 3D Affinity Learning and Agglomeration. CoRR (2017)
Marcel Nonnenmacher, Srinivas C. Turaga, Jakob H. Macke
Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlations. NIPS (2017)
Jan Funke, Fabian Tschopp, William Grisaitis, Arlo Sheridan, Chandan Singh, Stephan Saalfeld, Srinivas C. Turaga
A Deep Structured Learning Approach Towards Automating Connectome Reconstruction from 3D Electron Micrographs. CoRR (2017)
Artur Speiser, Jinyao Yan, Evan W. Archer, Lars Buesing, Srinivas C. Turaga, Jakob H. Macke
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders. NIPS (2017)
Artur Speiser, Jinyao Yan, Evan Archer, Lars Buesing, Srinivas C. Turaga, Jakob H. Macke
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders. CoRR (2017)
Laurence Aitchison, Lloyd Russell, Adam M. Packer, Jinyao Yan, Philippe Castonguay, Michael Häusser, Srinivas C. Turaga
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit. NIPS (2017)
Fabian Tschopp, Julien N. P. Martel, Srinivas C. Turaga, Matthew Cook, Jan Funke
Efficient convolutional neural networks for pixelwise classification on heterogeneous hardware systems. ISBI (2016)
Srinivas C. Turaga, Lars Buesing, Adam M. Packer, Henry Dalgleish, Noah Pettit, Michael Häusser, Jakob H. Macke
Inferring neural population dynamics from multiple partial recordings of the same neural circuit. NIPS (2013)
Viren Jain, Srinivas C. Turaga, Kevin L. Briggman, Moritz Helmstaedter, Winfried Denk, H. Sebastian Seung
Learning to Agglomerate Superpixel Hierarchies. NIPS (2011)
Srinivas C. Turaga, Joseph F. Murray, Viren Jain, Fabian Roth, Moritz Helmstaedter, Kevin L. Briggman, Winfried Denk, H. Sebastian Seung
Convolutional Networks Can Learn to Generate Affinity Graphs for Image Segmentation. Neural Comput. 22 (2) (2010)
Srinivas C. Turaga, Kevin L. Briggman, Moritz Helmstaedter, Winfried Denk, H. Sebastian Seung
Maximin affinity learning of image segmentation. NIPS (2009)
Srinivas C. Turaga, Kevin L. Briggman, Moritz Helmstaedter, Winfried Denk, H. Sebastian Seung
Maximin affinity learning of image segmentation CoRR (2009)
Viren Jain, Joseph F. Murray, Fabian Roth, Srinivas C. Turaga, Valentin P. Zhigulin, Kevin L. Briggman, Moritz Helmstaedter, Winfried Denk, H. Sebastian Seung
Supervised Learning of Image Restoration with Convolutional Networks. ICCV (2007)