Terrence J. Sejnowski

发表

The population tracking model: A simple, scalable statistical model for neural population data

Cian O'Donnell, J. Tiago Gonçalves, Nick Whiteley, 2016, bioRxiv.

Hidden Neural Networks

Terrence J. Sejnowski, Michael I. Jordan, 2001 .

The "Independent Components" of Scenes are Edge Filters

Terrence J. Sejnowski, Anthony J. Bell, A. J. Bell, 1997 .

Game-Theoretic Learning

Terrence J. Sejnowski, John G. McWhirter, Simon Haykin, 2007 .

Towards Biophysically-Based Neuromorphic Computing at Scale: Markov Abstractions of Electrochemical Reaction-Diffusion in Synaptic Transmission

Gert Cauwenberghs, Terrence J. Sejnowski, Margot Wagner, 2020 .

Diversity-enabled sweet spots in layered architectures and speed-accuracy trade-offs in sensorimotor control pdf

Terrence J. Sejnowski, Quanying Liu, John C. Doyle, 2019, ArXiv.

Multimodal classification of Parkinson’s disease using delay differential analysis

Terrence J. Sejnowski, Howard Poizner, Claudia Lainscsek, 2020, 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

What Makes a Dynamical System Computationally Powerful

Terrence J. Sejnowski, John G. McWhirter, Simon Haykin, 2007 .

Modeling Large Dynamical Systems with Dynamical Consistent Neural Networks

Terrence J. Sejnowski, John G. McWhirter, Simon Haykin, 2007 .

Non-Linear Dynamical Classification of Short Time Series of the Rössler System in High Noise Regimes

Terrence J. Sejnowski, Howard Poizner, Claudia Lainscsek, 2013, Front. Neurol..

AUTOMATIC ARTIFACT REJECTION FOR EEG DATA USING HIGH-ORDER STATISTICS AND INDEPENDENT COMPONENT ANALYSIS

Terrence J. Sejnowski, Arnaud Delorme, Scott Makeig, 2001 .

Toward Brain-Computer Interfacing (Neural Information Processing)

Terrence J. Sejnowski, José del R. Millán, Klaus-Robert Müller, 2007 .

The “independent components” of natural scenes are edge filters

Terrence J. Sejnowski, Anthony J. Bell, A. J. Bell, 1997, Vision Research.

Decision-making neural circuits mediating social behaviors - An attractor network model

Terrence J. Sejnowski, Julián Hurtado-López, David F. Ramirez-Moreno, 2017, J. Comput. Neurosci..

Modeling the molecular control of retinotopic map development and refinement

Terrence J. Sejnowski, Alex Holub, Paul A. Yates, 2004 .

Differential Covariance: A New Method to Estimate Functional Connectivity in fMRI

Terrence J. Sejnowski, Maxim Bazhenov, Giri P. Krishnan, 2020, Neural Computation.

Proceedings of the 1990 Summer School on Connectionist models

Terrence J. Sejnowski, David S. Touretzky, Jeffrey L. Elman, 1991 .

Neural network learning algorithms

Terrence J. Sejnowski, T. Sejnowski, 1988 .

Utilizing Deep Learning Towards Multi-Modal Bio-Sensing and Vision-Based Affective Computing pdf

Terrence J. Sejnowski, Tzyy-Ping Jung, Siddharth, 2019, IEEE Transactions on Affective Computing.

Parallel Networks that Learn to Pronounce

Terrence J. Sejnowski, Charles R. Rosenberg, T. Sejnowski, 1987 .

Nonlinear Time-Series Prediction with Missing and Noisy Data

Terrence J. Sejnowski, Michael I. Jordan, T. Sejnowski, 2001 .

Objective Functions for Topography: A Comparison of Optimal Maps

Terrence J. Sejnowski, Geoffrey J. Goodhill, 1997, NCPW.

9 Convolutional Learning

Terrence J. Sejnowski, 2018 .

The population tracking model: A simple, scalable statistical model for neural population data

Cian O'Donnell, J. Tiago Gonçalves, Nick Whiteley, 2016 .

HiCluster: A Robust Single-Cell Hi-C Clustering Method Based on Convolution and Random Walk

Terrence J. Sejnowski, Jian Peng, Jesse R. Dixon, 2018 .

Characterization of spatio-temporal epidural event-related potentials for mouse models of psychiatric disorders

Terrence J. Sejnowski, Xin Wang, António Pinto-Duarte, 2015, Scientific Reports.

A biologically inspired computational model of the Block Copying Task

Terrence J. Sejnowski, Marwan A. Jabri, Tian Lan, 2003 .

New Directions in Statistical Signal Processing: From Systems to Brains (Neural Information Processing)

Terrence J. Sejnowski, John G. McWhirter, Simon Haykin, 2006 .

Nonlinear blind source separation using kernel feature spaces

Terrence J. Sejnowski, Lee, Tzyy-Ping Jung, 2001 .

Decoupling the default mode network and global state oscillation by neural network-based prediction of the fMRI signal fluctuation

Terrence J. Sejnowski, Xin Yu, F Sobczak, 2020 .

Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources

Terrence J. Sejnowski, Te-Won Lee, Mark A. Girolami, 1999, Neural Comput..

Multivariate spectral analysis of electroencephalography data

Terrence J. Sejnowski, Howard Poizner, Claudia Lainscsek, 2013, 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER).

Correlation Coding in Stochastic Neural Networks

Terrence J. Sejnowski, Raphael Ritz, T. Sejnowski, 1997, ICANN.

Modeling the Mind: From Circuits to Systems

Terrence J. Sejnowski, John G. McWhirter, Simon Haykin, 2007 .

Dictionary Learning Algorithms for Sparse Representation

Joseph F. Murray, Terrence J. Sejnowski, Bhaskar D. Rao, 2003, Neural Computation.

Trajectories and Final Positions in Reaching Different Learned Coordinate Frames for Planning

Terrence J. Sejnowski, Allison M. Okamura, Ilana Nisky, 2015 .

Unsupervised Learning Of Invariant Representations Of Faces Through Temporal Association

Terrence J. Sejnowski, Marian Stewart Bartlett, T. Sejnowski, 1996 .

Connectionist Models: Proceedings of the Summer School Held in San Diego, California on 1990

Jeffrey L. Elman, Terrence J. Sejnowski, Geoffrey E. Hinton, 1990 .

Neural network models of sensory integration for improved vowel recognition

Terrence J. Sejnowski, Robert E. Jenkins, Ben P. Yuhas, 1990, Proc. IEEE.

Empirical Statistics and Stochastic Models for Visual Signals

Terrence J. Sejnowski, John G. McWhirter, Simon Haykin, 2007 .

Part IV. computational and mathematical considerations

Terrence J. Sejnowski, Patric K. Stanton, T. Sejnowski, 1990 .

A Variational Principle for Graphical Models

Terrence J. Sejnowski, John G. McWhirter, Simon Haykin, 2007 .

A modeling framework for adaptive lifelong learning with transfer and savings through gating in the prefrontal cortex

Hava T. Siegelmann, Terrence J. Sejnowski, Kay M. Tye, 2020, Proceedings of the National Academy of Sciences.

Exploration bonuses and dual control

Peter Dayan, Terrence J. Sejnowski, P. Dayan, 1996 .

LEARNING SEMANTIC FEATURES

Terrence J. Sejnowski, Geoffrey E. Hinton, 1984 .

Electrical Engineering (Intelligent Systems, Robotics, and Control)

Terrence J. Sejnowski, Nuno Vasconcelos, Charles Elkan, 2006 .

Differential covariance: A new method to estimate functional connectivity in fMRI

Terrence J. Sejnowski, Maxim Bazhenov, Giri P. Krishnan, 2017, bioRxiv.

Blind Signal Processing Based on Data Geometric Properties

Terrence J. Sejnowski, John G. McWhirter, Simon Haykin, 2007 .

Fitts' Law for speed-accuracy trade-off is a diversity sweet spot in sensorimotor control pdf

Terrence J. Sejnowski, Quanying Liu, John C. Doyle, 2019, ArXiv.

Variational Learning for Switching State-Space Models

Terrence J. Sejnowski, Michael I. Jordan, T. Sejnowski, 2001 .

Automated Medical Diagnosis based on Decision Theory and Learning from Cases

Terrence J. Sejnowski, Magnus Stensmo, Reimers Terry, 1996 .

Voyages through weight space: network models of an escape reflex in the leech

Terrence J. Sejnowski, Shawn R. Lockery, 1993 .

Efficient coding of color in natural scenes

Terrence J. Sejnowski, Te-Won Lee, Thomas Wachtler, 2005 .

The Machine Cocktail Party Problem

Terrence J. Sejnowski, John G. McWhirter, Simon Haykin, 2007 .

Separating figure from ground with a Boltzmann machine

Terrence J. Sejnowski, Geoffrey E. Hinton, Terrence J. Sejnowski, 1990 .

Models of Cortical Networks

Terrence J. Sejnowski, Paul C. Bush, T. Sejnowski, 1995 .

A Learning Algorithm for Boltzmann Machines

Terrence J. Sejnowski, Geoffrey E. Hinton, David H. Ackley, 1985, Cognitive Sciences.

Correctness of Local Probability Propagation in Graphical Models with Loops

Terrence J. Sejnowski, Michael I. Jordan, T. Sejnowski, 2001 .

Independent Factor Analysis

Terrence J. Sejnowski, Michael I. Jordan, 2009, Encyclopedia of Biometrics.

Unsupervised Learning

Terrence J. Sejnowski, Geoffrey E. Hinton, T. Sejnowski, 2018, Encyclopedia of GIS.

Designing Patterns for Easy Recognition: Information Transmission with Low-Density Parity-Check Codes

Terrence J. Sejnowski, John G. McWhirter, Simon Haykin, 2007 .

Simplifying network models of binocular rivalry and shape-from-shading

Terrence J. Sejnowski, Terrence J. Sejnowski, Sidney R. Lehky, 1989 .

NETtalk: a parallel network that learns to read aloud

Terrence J. Sejnowski, Charles R. Rosenberg, T. Sejnowski, 1988 .

Predicting Development Of Abnormal Standard Visual Fields In Ocular Hypertensive Eyes: Machine Learning Classifiers And Statpac-like Analysis

Terrence J. Sejnowski, T.–W. Lee, Pamela A. Sample, 2002 .

A Mixture Model Diagnosis System

Terrence J. Sejnowski, Magnus Stensmo, T. Sejnowski, 1994 .

Using Temporal-Difference Reinforcement Learning to Improve Decision-Theoretic Utilities for Diagnosis

Terrence J. Sejnowski, Magnus Stensmo, T. Sejnowski, 1995 .

Biological Clocks Coordinately Keep Life on Time

Terrence J. Sejnowski, Martha U. Gillette, T. Sejnowski, 2005, Science.

Series foreword

Terrence J. Sejnowski, Michael I. Jordan, Sara A. Solla, 2003 .

The Mind of a Mouse

Bruce R. Rosen, Terrence J. Sejnowski, Yann LeCun, 2020, Cell.

A Mixture Model Diagnosis

Terrence J. Sejnowski, T. Sejnowski, SystemMagnus, 1994 .