H. Sebastian Seung

Publication Activity (10 Years)

Years Active: 1991-2023
Publications (10 Years): 49

Top Topics

Unsupervised Learning

Normalized Cross Correlation

Electron Microscopy

Similarity Matching

Top Venues

Publications

Kyle Luther, H. Sebastian Seung
DDGM: Solving inverse problems by Diffusive Denoising of Gradient-based Minimization. CoRR (2023)
Kyle L. Luther, H. Sebastian Seung
Stretched sinograms for limited-angle tomographic reconstruction with neural networks. CoRR (2023)
Kyle Luther, H. Sebastian Seung
Stacked unsupervised learning with a network architecture found by supervised meta-learning. CoRR (2022)
Kyle Luther, H. Sebastian Seung
Sensitivity of sparse codes to image distortions. CoRR (2022)
Kyle Luther, H. Sebastian Seung
Kernel similarity matching with Hebbian networks. NeurIPS (2022)
Kyle Luther, H. Sebastian Seung
Sensitivity of Sparse Codes to Image Distortions. Neural Comput. 34 (7) (2022)
Jingpeng Wu, Nicholas L. Turner, J. Alexander Bae, Ashwin Vishwanathan, H. Sebastian Seung
RealNeuralNetworks.jl: An Integrated Julia Package for Skeletonization, Morphological Analysis, and Synaptic Connectivity Analysis of Terabyte-Scale 3D Neural Segmentations. Frontiers Neuroinformatics 16 (2022)
Kyle Luther, H. Sebastian Seung
Kernel similarity matching with Hebbian neural networks. CoRR (2022)
Ran Lu, Aleksandar Zlateski, H. Sebastian Seung
Large-scale image segmentation based on distributed clustering algorithms. CoRR (2021)
Kisuk Lee, Ran Lu, Kyle Luther, H. Sebastian Seung
Learning and Segmenting Dense Voxel Embeddings for 3D Neuron Reconstruction. IEEE Trans. Medical Imaging 40 (12) (2021)
Xiaoran Fan, Daewon Lee, Yuan Chen, Colin Prepscius, Volkan Isler, Larry D. Jackel, H. Sebastian Seung, Daniel D. Lee
Acoustic Collision Detection and Localization for Robot Manipulators. IROS (2020)
Nicholas L. Turner, Kisuk Lee, Ran Lu, Jingpeng Wu, Dodam Ih, H. Sebastian Seung
Synaptic Partner Assignment Using Attentional Voxel Association Networks. ISBI (2020)
Riley Simmons-Edler, Ben Eisner, Daniel Yang, Anthony Bisulco, Eric Mitchell, H. Sebastian Seung, Daniel D. Lee
Reward Prediction Error as an Exploration Objective in Deep RL. IJCAI (2020)
Sergiy Popovych, J. Alexander Bae, H. Sebastian Seung
Caesar: Segment-Wise Alignment Method for Solving Discontinuous Deformations. ISBI (2020)
H. Sebastian Seung
Convergence of gradient descent-ascent analyzed as a Newtonian dynamical system with dissipation. CoRR (2019)
Kyle Luther, H. Sebastian Seung
Variance-Preserving Initialization Schemes Improve Deep Network Training: But Which Variance is Preserved? CoRR (2019)
Tarik Tosun, Eric Mitchell, Ben Eisner, Jinwook Huh, Bhoram Lee, Daewon Lee, Volkan Isler, H. Sebastian Seung, Daniel D. Lee
Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner. CoRR (2019)
Nicholas L. Turner, Kisuk Lee, Ran Lu, Jingpeng Wu, Dodam Ih, H. Sebastian Seung
Synaptic Partner Assignment Using Attentional Voxel Association Networks. CoRR (2019)
Jingpeng Wu, William M. Silversmith, H. Sebastian Seung
Chunkflow: Distributed Hybrid Cloud Processing of Large 3D Images by Convolutional Nets. CoRR (2019)
Sergiy Popovych, Davit Buniatyan, Aleksandar Zlateski, Kai Li, H. Sebastian Seung
PZnet: Efficient 3D ConvNet Inference on Manycore CPUs. CVC (1) (2019)
Eric Mitchell, Stefan Keselj, Sergiy Popovych, Davit Buniatyan, H. Sebastian Seung
Siamese Encoding and Alignment by Multiscale Learning with Self-Supervision. CoRR (2019)
Kyle L. Luther, Runzhe Yang, H. Sebastian Seung
Unsupervised learning by a "softened" correlation game: duality and convergence. ACSSC (2019)
Riley Simmons-Edler, Ben Eisner, Eric Mitchell, H. Sebastian Seung, Daniel D. Lee
QXplore: Q-learning Exploration by Maximizing Temporal Difference Error. CoRR (2019)
Sergiy Popovych, Davit Buniatyan, Aleksandar Zlateski, Kai Li, H. Sebastian Seung
PZnet: Efficient 3D ConvNet Inference on Manycore CPUs. CoRR (2019)
Davit Buniatyan, Sergiy Popovych, Dodam Ih, Thomas Macrina, Jonathan Zung, H. Sebastian Seung
Weakly Supervised Deep Metric Learning for Template Matching. CVC (1) (2019)
James Gornet, Kannan Umadevi Venkataraju, Arun Narasimhan, Nicholas L. Turner, Kisuk Lee, H. Sebastian Seung, Pavel Osten, Uygar Sümbül
Reconstructing neuronal anatomy from whole-brain images. CoRR (2019)
Riley Simmons-Edler, Ben Eisner, Eric Mitchell, H. Sebastian Seung, Daniel D. Lee
Q-Learning for Continuous Actions with Cross-Entropy Guided Policies. CoRR (2019)
James Gornet, Kannan Umadevi Venkataraju, Arun Narasimhan, Nicholas L. Turner, Kisuk Lee, H. Sebastian Seung, Pavel Osten, Uygar Sümbül
Reconstructing Neuronal Anatomy from Whole-Brain Images. ISBI (2019)
Kyle Luther, H. Sebastian Seung
Learning Metric Graphs for Neuron Segmentation In Electron Microscopy Images. CoRR (2019)
Kyle Luther, H. Sebastian Seung
Learning Metric Graphs for Neuron Segmentation in Electron Microscopy Images. ISBI (2019)
Kisuk Lee, Nicholas L. Turner, Thomas Macrina, Jingpeng Wu, Ran Lu, H. Sebastian Seung
Convolutional nets for reconstructing neural circuits from brain images acquired by serial section electron microscopy. CoRR (2019)
Kisuk Lee, Ran Lu, Kyle Luther, H. Sebastian Seung
Learning Dense Voxel Embeddings for 3D Neuron Reconstruction. CoRR (2019)
Tarik Tosun, Eric Mitchell, Ben Eisner, Jinwook Huh, Bhoram Lee, Daewon Lee, Volkan Isler, H. Sebastian Seung, Daniel D. Lee
Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner. IROS (2019)
H. Sebastian Seung
Two "correlation games" for a nonlinear network with Hebbian excitatory neurons and anti-Hebbian inhibitory neurons. CoRR (2018)
H. Sebastian Seung
Unsupervised learning by a nonlinear network with Hebbian excitatory and anti-Hebbian inhibitory neurons. CoRR (2018)
Riley Simmons-Edler, Anders Miltner, H. Sebastian Seung
Program Synthesis Through Reinforcement Learning Guided Tree Search. CoRR (2018)
Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung
Scalable training of 3D convolutional networks on multi- and many-cores. J. Parallel Distributed Comput. 106 (2017)
Ignacio Arganda-Carreras, Verena Kaynig, Curtis Rueden, Kevin W. Eliceiri, Johannes E. Schindelin, Albert Cardona, H. Sebastian Seung
Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification. Bioinform. 33 (15) (2017)
Davit Buniatyan, Thomas Macrina, Dodam Ih, Jonathan Zung, H. Sebastian Seung
Deep Learning Improves Template Matching by Normalized Cross Correlation. CoRR (2017)
Aleksandar Zlateski, H. Sebastian Seung
Compile-time optimized and statically scheduled N-D convnet primitives for multi-core and many-core (Xeon Phi) CPUs. ICS (2017)
Jonathan Zung, Ignacio Tartavull, Kisuk Lee, H. Sebastian Seung
An Error Detection and Correction Framework for Connectomics. NIPS (2017)
Kisuk Lee, Jonathan Zung, Peter Li, Viren Jain, H. Sebastian Seung
Superhuman Accuracy on the SNEMI3D Connectomics Challenge. CoRR (2017)
Jonathan Zung, Ignacio Tartavull, H. Sebastian Seung
An Error Detection and Correction Framework for Connectomics. CoRR (2017)
H. Sebastian Seung, Jonathan Zung
A correlation game for unsupervised learning yields computational interpretations of Hebbian excitation, anti-Hebbian inhibition, and synapse elimination. CoRR (2017)
Noah J. Apthorpe, Alexander J. Riordan, Rob E. Aguilar, Jan Homann, Yi Gu, David W. Tank, H. Sebastian Seung
Automatic Neuron Detection in Calcium Imaging Data Using Convolutional Networks. NIPS (2016)
Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung
ZNNi - Maximizing the Inference Throughput of 3D Convolutional Networks on Multi-Core CPUs and GPUs. CoRR (2016)
Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung
ZNN - A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-core and Many-Core Shared Memory Machines. IPDPS (2016)
Noah J. Apthorpe, Alexander J. Riordan, Rob E. Aguilar, Jan Homann, Yi Gu, David W. Tank, H. Sebastian Seung
Automatic Neuron Detection in Calcium Imaging Data Using Convolutional Networks. CoRR (2016)
Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung
: maximizing the inference throughput of 3D convolutional networks on CPUs and GPUs. SC (2016)
Kisuk Lee, Aleksandar Zlateski, Ashwin Vishwanathan, H. Sebastian Seung
Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Prediction. NIPS (2015)
Aleksandar Zlateski, H. Sebastian Seung
Image Segmentation by Size-Dependent Single Linkage Clustering of a Watershed Basin Graph. CoRR (2015)
Kisuk Lee, Aleksandar Zlateski, Ashwin Vishwanathan, H. Sebastian Seung
Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Detection. CoRR (2015)
Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung
ZNN - A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-Core and Many-Core Shared Memory Machines. CoRR (2015)
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)
Viren Jain, Benjamin Bollmann, Mark Richardson, Daniel R. Berger, Moritz Helmstaedter, Kevin L. Briggman, Winfried Denk, Jared B. Bowden, John M. Mendenhall, Wickliffe C. Abraham, Kristen M. Harris, Narayanan Kasthuri, Ken J. Hayworth, Richard Schalek, Juan Carlos Tapia, Jeff W. Lichtman, H. Sebastian Seung
Boundary Learning by Optimization with Topological Constraints. CVPR (2010)
Srinivas C. Turaga, Kevin L. Briggman, Moritz Helmstaedter, Winfried Denk, H. Sebastian Seung
Maximin affinity learning of image segmentation. NIPS (2009)
Yonatan Loewenstein, Drazen Prelec, H. Sebastian Seung
Operant Matching as a Nash Equilibrium of an Intertemporal Game. Neural Comput. 21 (10) (2009)
Srinivas C. Turaga, Kevin L. Briggman, Moritz Helmstaedter, Winfried Denk, H. Sebastian Seung
Maximin affinity learning of image segmentation CoRR (2009)
Viren Jain, H. Sebastian Seung
Natural Image Denoising with Convolutional Networks. NIPS (2008)
Dezhe Z. Jin, Fethi M. Ramazanoglu, H. Sebastian Seung
Intrinsic bursting enhances the robustness of a neural network model of sequence generation by avian brain area HVC. J. Comput. Neurosci. 23 (3) (2007)
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)
Whitman Richards, H. Sebastian Seung, Galen Pickard
Neural voting machines. Neural Networks 19 (8) (2006)
Viren Jain, Valentin P. Zhigulin, H. Sebastian Seung
Representing Part-Whole Relationships in Recurrent Neural Networks. NIPS (2005)
Justin Werfel, Xiaohui Xie, H. Sebastian Seung
Learning Curves for Stochastic Gradient Descent in Linear Feedforward Networks. Neural Comput. 17 (12) (2005)
Brett D. Mensh, Justin Werfel, H. Sebastian Seung
BCI competition 2003-data set Ia: combining gamma-band power with slow cortical potentials to improve single-trial classification of electroencephalographic signals. IEEE Trans. Biomed. Eng. 51 (6) (2004)
Russ Tedrake, Teresa Weirui Zhang, H. Sebastian Seung
Stochastic policy gradient reinforcement learning on a simple 3D biped. IROS (2004)
Russ Tedrake, Teresa Weirui Zhang, Ming-fai Fong, H. Sebastian Seung
Actuating a Simple 3D Passive Dynamic Walker. ICRA (2004)
Richard H. R. Hahnloser, H. Sebastian Seung, Jean-Jacques E. Slotine
Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks. Neural Comput. 15 (3) (2003)
Justin Werfel, Xiaohui Xie, H. Sebastian Seung
Learning Curves for Stochastic Gradient Descent in Linear Feedforward Networks. NIPS (2003)
Xiaohui Xie, H. Sebastian Seung
Equivalence of Backpropagation and Contrastive Hebbian Learning in a Layered Network. Neural Comput. 15 (2) (2003)
Xiaohui Xie, Richard H. R. Hahnloser, H. Sebastian Seung
Selectively Grouping Neurons in Recurrent Networks of Lateral Inhibition. Neural Comput. 14 (11) (2002)
Richard H. R. Hahnloser, Xiaohui Xie, H. Sebastian Seung
A theory of neural integration in the head-direction system. NIPS (2001)
Xiaohui Xie, Richard H. R. Hahnloser, H. Sebastian Seung
Learning Winner-take-all Competition Between Groups of Neurons in Lateral Inhibitory Networks. NIPS (2000)
Richard H. R. Hahnloser, H. Sebastian Seung
Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks. NIPS (2000)
H. Sebastian Seung, Daniel D. Lee, Ben Y. Reis, David W. Tank
The Autapse: A Simple Illustration of Short-Term Analog Memory Storage by Tuned Synaptic Feedback. J. Comput. Neurosci. 9 (2) (2000)
Daniel D. Lee, H. Sebastian Seung
Algorithms for Non-negative Matrix Factorization. NIPS (2000)
Xiaohui Xie, H. Sebastian Seung
Spike-based Learning Rules and Stabilization of Persistent Neural Activity. NIPS (1999)
Daniel D. Lee, H. Sebastian Seung
Learning in Intelligent Embedded Systems. USENIX Workshop on Embedded Systems (1999)
H. Sebastian Seung
Continuous attractors and oculomotor control. Neural Networks 11 (7-8) (1998)
Jong-Hoon Oh, H. Sebastian Seung
Learning Generative Models with the Up-Propagation Algorithm. NIPS (1997)
Daniel D. Lee, H. Sebastian Seung
A Neural Network Based Head Tracking System. NIPS (1997)
Yoav Freund, H. Sebastian Seung, Eli Shamir, Naftali Tishby
Selective Sampling Using the Query by Committee Algorithm. Mach. Learn. 28 (2-3) (1997)
Nicholas D. Socci, Daniel D. Lee, H. Sebastian Seung
The Rectified Gaussian Distribution. NIPS (1997)
H. Sebastian Seung
Learning Continuous Attractors in Recurrent Networks. NIPS (1997)
H. Sebastian Seung, Tom J. Richardson, J. C. Lagarias, John J. Hopfield
Minimax and Hamiltonian Dynamics of Excitatory-Inhibitory Networks. NIPS (1997)
Daniel D. Lee, H. Sebastian Seung
Unsupervised Learning by Convex and Conic Coding. NIPS (1996)
David Haussler, Michael J. Kearns, H. Sebastian Seung, Naftali Tishby
Rigorous Learning Curve Bounds from Statistical Mechanics. Mach. Learn. 25 (2-3) (1996)
Michael J. Kearns, H. Sebastian Seung
Learning from a Population of Hypotheses. Mach. Learn. 18 (2-3) (1995)
N. Barkai, H. Sebastian Seung, Haim Sompolinsky
On-line Learning of Dichotomies. NIPS (1994)
David Haussler, H. Sebastian Seung, Michael J. Kearns, Naftali Tishby
Rigorous Learning Curve Bounds from Statistical Mechanics. COLT (1994)
Michael J. Kearns, H. Sebastian Seung
Learning from a Population of Hypotheses. COLT (1993)
Yoav Freund, H. Sebastian Seung, Eli Shamir, Naftali Tishby
Information, Prediction, and Query by Committee. NIPS (1992)
H. Sebastian Seung, Manfred Opper, Haim Sompolinsky
Query by Committee. COLT (1992)
H. Sebastian Seung, Haim Sompolinsky, Naftali Tishby
Learning Curves in Large Neural Networks. COLT (1991)